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IAEC2017/associacao.arff
@RELATION compras
@attribute leite {sim, nao}
@attribute ovos {sim, nao}
@attribute cafe {sim, nao}
@attribute acucar {sim, nao}
@attribute fraldas {sim, nao}
@attribute manteiga {sim, nao}
@attribute farinha {sim, nao}
@attribute cerveja {sim, nao}
@data
sim,sim,sim,sim,sim,sim,?,?
sim,?,sim,?,?,?,sim,?
sim,sim,?,sim,?,?,?,?
?,?,sim,sim,?,?,?,?
?,?,?,?,sim,?,?,?
sim,sim,?,?,?,sim,?,?
?,sim,?,?,?,sim,sim,?
sim,sim,sim,sim,?,sim,?,?
?,?,sim,?,sim,?,?,sim
IAEC2017/Prova (1).pdf
 UNIVERSIDADE FEDERAL DA GRANDE DOURADOS 
 
 
Primeira Avaliação Teórica – 08/11/2017 
--- Inteligência Artificial--- 
 
Nome:_______________________________________________________________________________ 
Orientações 
1. Guarde todo o material. Esta prova é individual e sem consulta. 
2. Desligue o celular. 
3. Leia atentamente o enunciado das questões e busque atender EXATAMENTE ao solicitado. 
4. Se tiver alguma dúvida, consulte o professor. 
5. Responda primeiramente as questões que você tem segurança na resposta. 
6. A nota máxima nesta prova é dez, mesmo quando a soma dos valores das questões supera essa nota. 
 
 
1. (Valor 1,5) Um espaço de estados finito conduz a uma árvore de busca finita? Justifique 
cuidadosamente a sua resposta. 
 
 
 
 
 
 
 
 
2. (Valor 1,5) O algoritmo de caminho heurístico é uma busca pela melhor escolha na qual a 
função objetivo é f(n) = (2-w)*g(n) + w*h(n). Para qual valor de w esse algoritmo se 
transforma no algoritmo A*? Que espécie de busca ele executa quando w = 0? 
 
 
 
 
 
 
 
 
 
 
 
 
 
3. (Valor 2,5) Considere a seguinte árvore de um jogo de soma zero, no qual as utilidades 
mostradas nos nós-folhas são para o primeiro jogador (A) que é um MAXimizador. 
Suponha que o segundo jogador (B) é um MINimizador. 
 
a) Escreva nos nós internos da árvore o valor de utilidade dos jogadores (isto é, o 
valor minimax desses nós). 
b) Circule as arestas da árvore correspondentes às jogadas escolhidas por A e por 
B de acordo com o valor minmax. 
c) Faça um X em cima dos nós que seriam podados pela poda alfa-beta, supondo 
que os nós são percorridos da esquerda para a direita. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 UNIVERSIDADE FEDERAL DA GRANDE DOURADOS 
 
 
4. (Valor 2,5) O Goku está prestes a encontrar a esfera do dragão de 4 estrelas! A esfera está 
localizada no final do labirinto. Goku deve encontrar um caminho para chegar até a esfera 
de 4 estrelas. O agente não pode se mover na diagonal, somente acima, abaixo, direita e 
esquerda. Ele também não pode atravessar paredes (as linhas mais grossas da grade) ou as 
bordas do labirinto, de modo que ele é forçado a contornar obstáculos. Felizmente, o 
Goku possui um mapa do ambiente. A solução é o caminho mais curto até a esfera e todos 
os movimentos possuem os mesmos custos. Estados sucessores devem ser dispostos na 
seguinte ordem: sul (S), oeste (O), norte (N), leste (L). 
 
 
a) Descreva o problema em termos de um problema de busca definindo o espaço 
de estados, o estado inicial, o estado final, os operadores de transição entre os 
estados (ações) e o custo. 
b) Construa um grafo do espaço de estados rotulando os arcos com os operadores 
de transição adequados. 
c) Em qual ordem uma busca em profundidade visita as salas do labirinto. 
d) Em qual ordem uma busca em largura visita as salas do labirinto. 
 
 
 
 
 
 
 
Cont. 4: 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 UNIVERSIDADE FEDERAL DA GRANDE DOURADOS 
 
 
5. Valor (2,0) A partir dos dados abaixo, classifique a última instância com algoritmo KNN 
para os valores de K=1,2,3,4 e 5, usando função de distância Euclediana. 
 
 
 
 
 
 
 
 
 
 
 
IAEC2017/Lista 2.pdf
Inteligência Artificial 
Willian P. Amorim 
Lista de Exercícios 2 
 
 
1. Apresente o passo-a-passo para a criação da árvore de decisão, baseado no algoritmo ID3, a partir 
dos dados de aprendizagem abaixo. 
 
 
 
 
 
2. A partir dos dados abaixo, aplique o algoritmo de k-means e apresente o resultado do agrupamento 
das amostras, considerando k = 2. A semente 1 está na posição (4.1, 5.4) e semente 2 está na 
posição (1.8, 2.3). 
 
 
 
 
 
3. A Tabela 3 mostra um conjunto de exemplos de treinamento utilizados por um algoritmo de AM 
i.e. o número de exemplos (#Ex.), número e porcentagem de exemplos duplicados (que aparecem 
mais de uma vez) e/ou conflitantes (mesmos valores dos atributos mas classificações (diferentes), 
número de atributos (#Atrib.) contínuos e nominais, distribuição das classes, erro majoritário e se 
o conjunto de dados tem pelo menos um valor desconhecido (Valores Desconh.) A Tabela 4 
ilustra a matriz de confusão para um problema de classificação de duas classes (considere que 
“resolvido” corresponde aos exemplos positivos, ou C+, e “no resolvido” aos exemplos negativos, 
ou C−) onde TP é o número de exemplos positivos classificados corretamente e FN é o número 
de exemplos positivos classificados de forma errada em um total de n = (TP + FN + FP + TN ) 
exemplos. As taxas nessa tabela referem-se a: a taxa de erro relativo 1a classe positiva, ou a 
especificidade (Equação 1); a taxa de erro relativo à classe negativa, também conhecida como 
sensitividade (Equação 2) e o erro total (Equação 3). 
 
 
 
 
 
 
Dois algoritmos diferentes (A1 e A2) de AM foram utilizados para induzir hipóteses. A fim 
de medir o erro verdadeiro foi utilizado o método 5-cross validation. As Tabelas 5 e 6 mos-
tram, respectivamente, os resultados obtidos com cada fold (100 exemplos por fold) para o 
classificador induzido pelo algoritmo A1 e pelo algoritmo A2. 
 
 
 
 
 
Calcule os valores dados pelas equações 1), 2) e 3) para cada fold (colocar o resultado no lugar 
correspondente da tabela de cada algoritmo). Calcule a média e o desvio padrão das três taxas de 
erro. 
 
 
4. Considere o diâmetro e peso de 10 amostras de rochas. Apresente a fórmula de regressão linear 
para a previsão de valores do peso da rocha. 
 
 
 
5. Considere os seguintes pontos, abaixo: 
 
Aplique o algoritmo de k-means e apresente o resultado do agrupamento das amostras, 
considerando k = 2. A semente 1 está na posição P2 e semente 2 está na posição P8. Aplique 
novamente k-means sobre o conjunto original, usando k = 2. A semente 1 está na posição P7 e 
semente 2 está na posição P4. Análise o comportamento das duas execuções de k-means. 
 
 
6. Para os seguintes dados: 
 
 
(a) Calcular as distâncias Euclidianas. 
 
(b) Montar a matriz de distâncias. 
 
(c) Utilizando agrupamento hierárquico (modelo bottom-up), construir o dendograma. 
IAEC2017/Prova (2).pdf
 UNIVERSIDADE FEDERAL DA GRANDE DOURADOS 
 
 
Segunda Avaliação Teórica – 07/02/2018
--- Inteligência Artificial--- 
 
Nome:_______________________________________________________________________________ 
Orientações 
1. Guarde todo o material. Esta prova é individual e sem consulta. 
2. Desligue o celular. 
3. Leia atentamente o enunciado das questões e busque atender EXATAMENTE ao solicitado. 
4. Se tiver alguma dúvida, consulte o professor. 
5. Responda primeiramente as questões que você tem segurança na resposta. 
6. A nota máxima nesta prova é dez, mesmo quando a soma dos valores das questões supera essa nota. 
 
 
1. (Valor 2,0) Considere o resultado do aprendizado sobre qualquer entrada a árvore de decisão 
abaixo. 
Árvore de decisão 
 
 Conjunto de teste 
Clima Temperatura Umidade Vento Jogar? 
Sol Normal Alta Verdadeiro Não 
Nublado Quente Alta Verdadeiro Sim 
Nublado Quente Alta Falso Não 
Chuvoso Suave Normal Falso Sim 
Chuvoso Normal Normal Verdadeiro Não 
Chuvoso Quente Alta Falso Não 
 
a) Usando o método de amostragem “Cross-Validation”, apresente o erro médio 
final e desvio padrão na classificação do conjunto de teste com fold = 3 (valor 
de r), seguindo a mesma ordem de apresentação para partição. 
 
 
 
 
b) Usando o método de amostragem “Leave-one-out”, teremos o erro médio final 
igual ou diferente adotado por “Cross-Validation”? Explique. 
 
 
 
2. (Valor 2,0) Considere o rendimento em um processo químico com relação a sua 
temperatura. Apresente a fórmula de regressão linear para a previsão dos valores de 
rendimento. 
Temperatura ºC 0 25 50 75 100 
Rendimento 14 38 54 76 95 
 
 
 
 
 
 
 
 
 
 
 UNIVERSIDADE FEDERAL DA GRANDE DOURADOS 
 
 
3. (Valor 3,0) Use o algoritmo k-means e a distância euclidiana, seguindo os pontos das 
coordenadas na ordem P(X,Y) para agrupar os seguintes exemplos abaixo. Considere 
k=3, sendo as sementes iniciais nas coordenadas A1, A4 e A7: 
 
 
 
 
4. (Valor 3,0) Apresente o passo-a-passo para a criação da árvore de decisão, baseado no 
algoritmo ID3, a partir dos dados de aprendizagem abaixo. 
 
 
 
 
 
 
 
 
 
 
Identificador Febre Vômito Diarreia Tremor Classificação 
Amostra 1 Não Não Não Não Saudável 
Amostra 2 Média Não Não Não Gripe 
Amostra 3 Alta Não Não Sim Gripe 
Amostra 4 Alta Sim Sim Não Infecção 
Amostra 5 Média Não Sim Não Infecção 
Amostra 6 Não Sim Sim Não Inflamação 
Amostra 7 Média Sim Sim Não Inflamação 
IAEC2017/regressao.arff
@RELATION house 
@ATTRIBUTE houseSize NUMERIC 
@ATTRIBUTE lotSize NUMERIC 
@ATTRIBUTE bedrooms NUMERIC 
@ATTRIBUTE granite NUMERIC 
@ATTRIBUTE bathroom NUMERIC 
@ATTRIBUTE sellingPrice NUMERIC 
@DATA 
3529,9191,6,0,0,205000 
3247,10061,5,1,1,224900 
4032,10150,5,0,1,197900 
2397,14156,4,1,0,189900 
2200,9600,4,0,1,195000
3536,19994,6,1,1,325000 
2983,9365,5,0,1,230000
IAEC2017/iris.arff
% 1. Title: Iris Plants Database
% 
% 2. Sources:
% (a) Creator: R.A. Fisher
% (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)
% (c) Date: July, 1988
% 
% 3. Past Usage:
% - Publications: too many to mention!!! Here are a few.
% 1. Fisher,R.A. "The use of multiple measurements in taxonomic problems"
% Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions
% to Mathematical Statistics" (John Wiley, NY, 1950).
% 2. Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis.
% (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218.
% 3. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System
% Structure and Classification Rule for Recognition in Partially Exposed
% Environments". IEEE Transactions on Pattern Analysis and Machine
% Intelligence, Vol. PAMI-2, No. 1, 67-71.
% -- Results:
% -- very low misclassification rates (0% for the setosa class)
% 4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE 
% Transactions on Information Theory, May 1972, 431-433.
% -- Results:
% -- very low misclassification rates again
% 5. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II
% conceptual clustering system finds 3 classes in the data.
% 
% 4. Relevant Information:
% --- This is perhaps the best known database to be found in the pattern
% recognition literature. Fisher's paper is a classic in the field
% and is referenced frequently to this day. (See Duda & Hart, for
% example.) The data set contains 3 classes of 50 instances each,
% where each class refers to a type of iris plant. One class is
% linearly separable from the other 2; the latter are NOT linearly
% separable from each other.
% --- Predicted attribute: class of iris plant.
% --- This is an exceedingly simple domain.
% 
% 5. Number of Instances: 150 (50 in each of three classes)
% 
% 6. Number of Attributes: 4 numeric, predictive attributes and the class
% 
% 7. Attribute Information:
% 1. sepal length in cm
% 2. sepal width in cm
% 3. petal length in cm
% 4. petal width in cm
% 5. class: 
% -- Iris Setosa
% -- Iris Versicolour
% -- Iris Virginica
% 
% 8. Missing Attribute Values: None
% 
% Summary Statistics:
% 	 Min Max Mean SD Class Correlation
% sepal length: 4.3 7.9 5.84 0.83 0.7826 
% sepal width: 2.0 4.4 3.05 0.43 -0.4194
% petal length: 1.0 6.9 3.76 1.76 0.9490 (high!)
% petal width: 0.1 2.5 1.20 0.76 0.9565 (high!)
% 
% 9. Class Distribution: 33.3% for each of 3 classes.
@RELATION iris
@ATTRIBUTE sepallength	REAL
@ATTRIBUTE sepalwidth 	REAL
@ATTRIBUTE petallength 	REAL
@ATTRIBUTE petalwidth	REAL
@ATTRIBUTE class 	{Iris-setosa,Iris-versicolor,Iris-virginica}
@DATA
5.1,3.5,1.4,0.2,Iris-setosa
4.9,3.0,1.4,0.2,Iris-setosa
4.7,3.2,1.3,0.2,Iris-setosa
4.6,3.1,1.5,0.2,Iris-setosa
5.0,3.6,1.4,0.2,Iris-setosa
5.4,3.9,1.7,0.4,Iris-setosa
4.6,3.4,1.4,0.3,Iris-setosa
5.0,3.4,1.5,0.2,Iris-setosa
4.4,2.9,1.4,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
5.4,3.7,1.5,0.2,Iris-setosa
4.8,3.4,1.6,0.2,Iris-setosa
4.8,3.0,1.4,0.1,Iris-setosa
4.3,3.0,1.1,0.1,Iris-setosa
5.8,4.0,1.2,0.2,Iris-setosa
5.7,4.4,1.5,0.4,Iris-setosa
5.4,3.9,1.3,0.4,Iris-setosa
5.1,3.5,1.4,0.3,Iris-setosa
5.7,3.8,1.7,0.3,Iris-setosa
5.1,3.8,1.5,0.3,Iris-setosa
5.4,3.4,1.7,0.2,Iris-setosa
5.1,3.7,1.5,0.4,Iris-setosa
4.6,3.6,1.0,0.2,Iris-setosa
5.1,3.3,1.7,0.5,Iris-setosa
4.8,3.4,1.9,0.2,Iris-setosa
5.0,3.0,1.6,0.2,Iris-setosa
5.0,3.4,1.6,0.4,Iris-setosa
5.2,3.5,1.5,0.2,Iris-setosa
5.2,3.4,1.4,0.2,Iris-setosa
4.7,3.2,1.6,0.2,Iris-setosa
4.8,3.1,1.6,0.2,Iris-setosa
5.4,3.4,1.5,0.4,Iris-setosa
5.2,4.1,1.5,0.1,Iris-setosa
5.5,4.2,1.4,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
5.0,3.2,1.2,0.2,Iris-setosa
5.5,3.5,1.3,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
4.4,3.0,1.3,0.2,Iris-setosa
5.1,3.4,1.5,0.2,Iris-setosa
5.0,3.5,1.3,0.3,Iris-setosa
4.5,2.3,1.3,0.3,Iris-setosa
4.4,3.2,1.3,0.2,Iris-setosa
5.0,3.5,1.6,0.6,Iris-setosa
5.1,3.8,1.9,0.4,Iris-setosa
4.8,3.0,1.4,0.3,Iris-setosa
5.1,3.8,1.6,0.2,Iris-setosa
4.6,3.2,1.4,0.2,Iris-setosa
5.3,3.7,1.5,0.2,Iris-setosa
5.0,3.3,1.4,0.2,Iris-setosa
7.0,3.2,4.7,1.4,Iris-versicolor
6.4,3.2,4.5,1.5,Iris-versicolor
6.9,3.1,4.9,1.5,Iris-versicolor
5.5,2.3,4.0,1.3,Iris-versicolor
6.5,2.8,4.6,1.5,Iris-versicolor
5.7,2.8,4.5,1.3,Iris-versicolor
6.3,3.3,4.7,1.6,Iris-versicolor
4.9,2.4,3.3,1.0,Iris-versicolor
6.6,2.9,4.6,1.3,Iris-versicolor
5.2,2.7,3.9,1.4,Iris-versicolor
5.0,2.0,3.5,1.0,Iris-versicolor
5.9,3.0,4.2,1.5,Iris-versicolor
6.0,2.2,4.0,1.0,Iris-versicolor
6.1,2.9,4.7,1.4,Iris-versicolor
5.6,2.9,3.6,1.3,Iris-versicolor
6.7,3.1,4.4,1.4,Iris-versicolor
5.6,3.0,4.5,1.5,Iris-versicolor
5.8,2.7,4.1,1.0,Iris-versicolor
6.2,2.2,4.5,1.5,Iris-versicolor
5.6,2.5,3.9,1.1,Iris-versicolor
5.9,3.2,4.8,1.8,Iris-versicolor
6.1,2.8,4.0,1.3,Iris-versicolor
6.3,2.5,4.9,1.5,Iris-versicolor
6.1,2.8,4.7,1.2,Iris-versicolor
6.4,2.9,4.3,1.3,Iris-versicolor
6.6,3.0,4.4,1.4,Iris-versicolor
6.8,2.8,4.8,1.4,Iris-versicolor
6.7,3.0,5.0,1.7,Iris-versicolor
6.0,2.9,4.5,1.5,Iris-versicolor
5.7,2.6,3.5,1.0,Iris-versicolor
5.5,2.4,3.8,1.1,Iris-versicolor
5.5,2.4,3.7,1.0,Iris-versicolor
5.8,2.7,3.9,1.2,Iris-versicolor
6.0,2.7,5.1,1.6,Iris-versicolor
5.4,3.0,4.5,1.5,Iris-versicolor
6.0,3.4,4.5,1.6,Iris-versicolor
6.7,3.1,4.7,1.5,Iris-versicolor
6.3,2.3,4.4,1.3,Iris-versicolor
5.6,3.0,4.1,1.3,Iris-versicolor
5.5,2.5,4.0,1.3,Iris-versicolor
5.5,2.6,4.4,1.2,Iris-versicolor
6.1,3.0,4.6,1.4,Iris-versicolor
5.8,2.6,4.0,1.2,Iris-versicolor
5.0,2.3,3.3,1.0,Iris-versicolor
5.6,2.7,4.2,1.3,Iris-versicolor
5.7,3.0,4.2,1.2,Iris-versicolor
5.7,2.9,4.2,1.3,Iris-versicolor
6.2,2.9,4.3,1.3,Iris-versicolor
5.1,2.5,3.0,1.1,Iris-versicolor
5.7,2.8,4.1,1.3,Iris-versicolor
6.3,3.3,6.0,2.5,Iris-virginica
5.8,2.7,5.1,1.9,Iris-virginica
7.1,3.0,5.9,2.1,Iris-virginica
6.3,2.9,5.6,1.8,Iris-virginica
6.5,3.0,5.8,2.2,Iris-virginica
7.6,3.0,6.6,2.1,Iris-virginica
4.9,2.5,4.5,1.7,Iris-virginica
7.3,2.9,6.3,1.8,Iris-virginica
6.7,2.5,5.8,1.8,Iris-virginica
7.2,3.6,6.1,2.5,Iris-virginica
6.5,3.2,5.1,2.0,Iris-virginica
6.4,2.7,5.3,1.9,Iris-virginica
6.8,3.0,5.5,2.1,Iris-virginica
5.7,2.5,5.0,2.0,Iris-virginica
5.8,2.8,5.1,2.4,Iris-virginica
6.4,3.2,5.3,2.3,Iris-virginica
6.5,3.0,5.5,1.8,Iris-virginica
7.7,3.8,6.7,2.2,Iris-virginica
7.7,2.6,6.9,2.3,Iris-virginica
6.0,2.2,5.0,1.5,Iris-virginica
6.9,3.2,5.7,2.3,Iris-virginica
5.6,2.8,4.9,2.0,Iris-virginica
7.7,2.8,6.7,2.0,Iris-virginica
6.3,2.7,4.9,1.8,Iris-virginica
6.7,3.3,5.7,2.1,Iris-virginica
7.2,3.2,6.0,1.8,Iris-virginica
6.2,2.8,4.8,1.8,Iris-virginica
6.1,3.0,4.9,1.8,Iris-virginica
6.4,2.8,5.6,2.1,Iris-virginica
7.2,3.0,5.8,1.6,Iris-virginica
7.4,2.8,6.1,1.9,Iris-virginica
7.9,3.8,6.4,2.0,Iris-virginica
6.4,2.8,5.6,2.2,Iris-virginica
6.3,2.8,5.1,1.5,Iris-virginica
6.1,2.6,5.6,1.4,Iris-virginica
7.7,3.0,6.1,2.3,Iris-virginica
6.3,3.4,5.6,2.4,Iris-virginica
6.4,3.1,5.5,1.8,Iris-virginica
6.0,3.0,4.8,1.8,Iris-virginica
6.9,3.1,5.4,2.1,Iris-virginica
6.7,3.1,5.6,2.4,Iris-virginica
6.9,3.1,5.1,2.3,Iris-virginica
5.8,2.7,5.1,1.9,Iris-virginica
6.8,3.2,5.9,2.3,Iris-virginica
6.7,3.3,5.7,2.5,Iris-virginica
6.7,3.0,5.2,2.3,Iris-virginica
6.3,2.5,5.0,1.9,Iris-virginica
6.5,3.0,5.2,2.0,Iris-virginica
6.2,3.4,5.4,2.3,Iris-virginica
5.9,3.0,5.1,1.8,Iris-virginica
%
%
%
IAEC2017/Aula 8-1.pdf
IAEC2017/Aula 8-2.pptx
Aula 8
Weka – Regressão - Associação
Regressão 
 • A análise de regressão entende-se como previsão. Quando fazemos uma regressão, queremos prever Resultados.
A análise de dados através de regressão linear está entre as técnicas mais utilizadas para construção de modelos para descrever o comportamento de uma variável dependente.
 Fórmula da regressão linear: Y = ax + b, sendo x a variável independente e y a variável dependente.
 Técnica usada para estimar a condicional (valor esperado) de uma variável y, dados os valores de algumas outras variáveis x.
Regressão 
 Regressão em geral busca estimar um valor condicional esperado.
 O modelo de regressão é então usado para prever o resultado de uma variável dependente desconhecida, dados os valores das variáveis independentes.
Regressão - Exemplo
Criando arquivo arff...
@RELATION house 
@ATTRIBUTE houseSize NUMERIC 
@ATTRIBUTE lotSize NUMERIC 
@ATTRIBUTE bedrooms NUMERIC 
@ATTRIBUTE granite NUMERIC 
@ATTRIBUTE bathroom NUMERIC 
@ATTRIBUTE sellingPrice NUMERIC 
@DATA 
3529,9191,6,0,0,205000 
3247,10061,5,1,1,224900 
4032,10150,5,0,1,197900 
2397,14156,4,1,0,189900 
2200,9600,4,0,1,195000
3536,19994,6,1,1,325000 
2983,9365,5,0,1,230000
Regressão - Exemplo
Weka
Regressão - Exemplo
Selecionando opção...
Regressão - Exemplo
Aplicando regressão...
Correlation coeficiente: indica a força e a direção do relacionamento linear entre duas variáveis aleatórias.
Mean absolute erro: é calculado como sendo a diferença entre valor experimental ou medido e o valor adotado que no caso é o valor médio.
Regressão - Exemplo
Associação
A técnica de associação é uma técnica exploratória.
A associação gera regras que descrevem os padrões mais relevantes presentes nos dados. 
As regras são compostas por:
Precedentes: Subconjunto de atributos e seus valores.
Consequentes: Subconjunto de atributos que decorrem do precedente.
Exemplo: Quem compra ovos, manteiga, farinha de trigo e chocolate também compra fermento.
Associação
Regras de Classificação: Predizem o valor de um atributo (a classificação do exemplo) 
Regras de Associação: Predizem o valor de um atributo arbitrário (ou combinação)
If outlook = sunny and humidity = high
then play = no
If temperature = cool then humidity = normal
If humidity = normal and windy = false
then play = yes
If outlook = sunny and play = no 
then humidity = high
If windy = false and play = no 
then outlook = sunny and humidity = high
Associação - Prática
% Compras em um mercado
@RELATION compras
@attribute leite {sim, não}
@attribute ovos {sim, não}
@attribute café {sim, não}
@attribute açúcar {sim, não}
@attribute fraldas {sim, não}
@attribute manteiga {sim, não}
@attribute farinha {sim, não}
@attribute cerveja {sim, não}
@data
sim,sim,sim,sim,sim,sim,não,não
sim,não,sim,não,não,não,sim,não
sim,sim,não,sim,não,não,não,não
não,não,sim,sim,não,não,não,não
não,não,não,não,sim,não,não,não
sim,sim,não,não,não,sim,não,não
não,sim,não,não,não,sim,sim,não
sim,sim,sim,sim,não,sim,não,não
não,não,sim,não,sim,não,não,sim
Algoritmo Apriori
Associação - Prática
Por default a execução do algoritmo tenta criar 10 regras de associação, ordenadas por confiança.
Resultado - Apriori
Associação - Prática
Indicação de itens ausentes: este é o detalhe mais importante. 
Se o " ? " não for utilizado, a Weka acaba minerando regras envolvendo itens ausentes, o que é bastante inconveniente.
Resultado - Apriori
IAEC2017/Aula5-Parte22.pdf
Inteligência Computacional
Prof. Willian P. Amorim
Árvore de Decisão – ID3
• Qual é o melhor atributo? Deveria ser aquele que 
mais “ajuda” na classificação
• Conceito importantes: Information Gain e 
Entropy
• Information Gain: Medida que indica o quanto 
um dado atributo irá separar os exemplos de 
aprendizado de acordo com a sua função objetivo 
(classes). Valor numérico - quantifica o ganho! 
Para determinar o ganho, precisamos calcular a 
“entropia” dos dados antes...
Árvore de Decisão – ID3
• Entropy: Medida que indica a homogenidade dos 
exemplos contidos em um conjunto de dados.
• Permite caracterizar a “pureza” (e impureza) de uma 
coleção arbitrária de exemplos.
• Dado o conjunto S, contendo exemplo ‘+’ e ‘-’ que 
definem o conceito a ser aprendido, a entropia 
relativa dos dados deste conjunto S é indicada por:
Árvore de Decisão – ID3
• Algoritmo ID3: Entropy
– P+ = Proporção entre os exemplos positivos e o total de 
exemplos do conjunto: 
Nrº. de Casos Positivos / Nrº. Total de Casos
– P- = Proporção entre os exemplos negativos e o total de 
exemplos do conjunto: 
Nrº. de Casos Negativos / Nrº. Total de Casos
– Sendo que: 0 . Log2 0 = 0 por definição.
• Exemplo: Baseado no conjunto
de dados “play tennis”
• P+ = 9/14 e P- = 5/14
Árvore de Decisão – ID3
• Exemplo: Baseado no conjunto de dados “play tennis”
P+ = 9/14 e P- = 5/14
Árvore de Decisão – ID3
• Logo, na base de 14 exemplos, onde 9 são positivos (Yes) e 5 
são negativos (No),
teremos...
• Entropy (Splay_tennis) = 0.94028595
Árvore de Decisão – ID3
• Algoritmo ID3: Entropy
• Fórmula para N classes:
Árvore de Decisão – ID3
• Algoritmo ID3: Entropy
• GAIN (S, A) = Redução esperada na entropia de S, causada pelo 
particionamento dos exemplos em relação a um atributo escolhido (A).
onde,
• A = Atributo considerado
• N = Número de valores possíveis que este atributo pode assumir
• Sv = Sub-conjunto de S onde o atributo A possui o valor V
Árvore de Decisão – ID3
• Algoritmo ID3: Entropy
• Exemplo: dado o atributo Wind = { weak, strong } da tabela “play tennis”
Gain(S, Wind) = Entropy(S) - ( PWeak .Entropy(SWind=Weak) + PStrong .Entropy(SWind=Strong) ) 
= 0.940 - ( 8/14 . Entropy(SWind=Weak) + 6/14 . Entropy(SWind=Strong) ) 
= 0.940 - (8/14.(-6/8.Log2(6/8)-2/8.Log2(2/8))) - (6/14.(-3/6.Log2(3/6)-3/6.Log2(3/6))
= 0.940 - 0.4634 - 0.4285 = 0.048
Árvore de Decisão – ID3
• Algoritmo ID3: Entropy
• Exemplo da tabela “play tennis”
– Gain(S, Outlook) = 0.246
– Gain(S, Humidity) = 0.151
– Gain(S, Wind) = 0.048
– Gain(S, Temperature) = 0.029
• Qual o melhor ganho?
– Certamente a escolha do atributo “outlook” maximiza o ganho!
Árvore de Decisão – ID3
Árvore de Decisão – ID3
• Exemplo para decidir atividade de final de semana.
Árvore de Decisão – ID3
• Exemplo
1º passo – calcular entropia de S(conjunto de dados)
2º passo – calcular o ganho para cada atributo.
Sendo o atributo selecionado com maior ganho (Gain)
Árvore de Decisão – ID3
• Exemplo
3º passo – árvore resultante do primeiro atributo selecionado
4º passo – Analisar cada possível valor do atributo selecionado.
Árvore de Decisão – ID3
• Exemplo
5º passo – calcular o ganho para cada 
possível valor de Weather-Sunny, para 
encontrar o melhor atributo.
IAEC2017/Aula7.pdf
IAEC2017/Aula5-Parte11.pdf
IAEC2017/weka.jar
META-INF/MANIFEST.MF
Manifest-Version: 1.0
Ant-Version: Apache Ant 1.8.2
Created-By: 1.7.0_21-b12 (Oracle Corporation)
Main-Class: weka.gui.GUIChooser
java_cup/runtime/ComplexSymbolFactory$ComplexSymbol.class
package java_cup.runtime;
public synchronized class ComplexSymbolFactory$ComplexSymbol extends Symbol {
 protected String name;
 protected ComplexSymbolFactory$Location xleft;
 protected ComplexSymbolFactory$Location xright;
 public void ComplexSymbolFactory$ComplexSymbol(String, int);
 public void ComplexSymbolFactory$ComplexSymbol(String, int, Object);
 public String toString();
 public void ComplexSymbolFactory$ComplexSymbol(String, int, int);
 public void ComplexSymbolFactory$ComplexSymbol(String, int, Symbol, Symbol);
 public void ComplexSymbolFactory$ComplexSymbol(String, int, ComplexSymbolFactory$Location, ComplexSymbolFactory$Location);
 public void ComplexSymbolFactory$ComplexSymbol(String, int, Symbol, Symbol, Object);
 public void ComplexSymbolFactory$ComplexSymbol(String, int, ComplexSymbolFactory$Location, ComplexSymbolFactory$Location, Object);
 public ComplexSymbolFactory$Location getLeft();
 public ComplexSymbolFactory$Location getRight();
}
java_cup/runtime/ComplexSymbolFactory$Location.class
package java_cup.runtime;
public synchronized class ComplexSymbolFactory$Location {
 private String unit;
 private int line;
 private int column;
 public void ComplexSymbolFactory$Location(String, int, int);
 public void ComplexSymbolFactory$Location(int, int);
 public String toString();
 public int getColumn();
 public int getLine();
 public String getUnit();
}
java_cup/runtime/ComplexSymbolFactory.class
package java_cup.runtime;
public synchronized class ComplexSymbolFactory implements SymbolFactory {
 public void ComplexSymbolFactory();
 public Symbol newSymbol(String, int, ComplexSymbolFactory$Location, ComplexSymbolFactory$Location, Object);
 public Symbol newSymbol(String, int, ComplexSymbolFactory$Location, ComplexSymbolFactory$Location);
 public Symbol newSymbol(String, int, Symbol, Symbol, Object);
 public Symbol newSymbol(String, int, Symbol, Symbol);
 public Symbol newSymbol(String, int);
 public Symbol newSymbol(String, int, Object);
 public Symbol startSymbol(String, int, int);
}
java_cup/runtime/DefaultSymbolFactory.class
package java_cup.runtime;
public synchronized class DefaultSymbolFactory implements SymbolFactory {
 public void DefaultSymbolFactory();
 public Symbol newSymbol(String, int, Symbol, Symbol, Object);
 public Symbol newSymbol(String, int, Symbol, Symbol);
 public Symbol newSymbol(String, int, int, int, Object);
 public Symbol newSymbol(String, int, int, int);
 public Symbol startSymbol(String, int, int);
 public Symbol newSymbol(String, int);
 public Symbol newSymbol(String, int, Object);
}
java_cup/runtime/Scanner.class
package java_cup.runtime;
public abstract interface Scanner {
 public abstract Symbol next_token() throws Exception;
}
java_cup/runtime/Symbol.class
package java_cup.runtime;
public synchronized class Symbol {
 public int sym;
 public int parse_state;
 boolean used_by_parser;
 public int left;
 public int right;
 public Object value;
 public void Symbol(int, Symbol, Symbol, Object);
 public void Symbol(int, Symbol, Symbol);
 public void Symbol(int, int, int, Object);
 public void Symbol(int, Object);
 public void Symbol(int, int, int);
 public void Symbol(int);
 void Symbol(int, int);
 public String toString();
}
java_cup/runtime/SymbolFactory.class
package java_cup.runtime;
public abstract interface SymbolFactory {
 public abstract Symbol newSymbol(String, int, Symbol, Symbol, Object);
 public abstract Symbol newSymbol(String, int, Symbol, Symbol);
 public abstract Symbol newSymbol(String, int, Object);
 public abstract Symbol newSymbol(String, int);
 public abstract Symbol startSymbol(String, int, int);
}
java_cup/runtime/lr_parser.class
package java_cup.runtime;
public abstract synchronized class lr_parser {
 public SymbolFactory symbolFactory;
 protected static final int _error_sync_size = 3;
 protected boolean _done_parsing;
 protected int tos;
 protected Symbol cur_token;
 protected java.util.Stack stack;
 protected short[][] production_tab;
 protected short[][] action_tab;
 protected short[][] reduce_tab;
 private Scanner _scanner;
 protected Symbol[] lookahead;
 protected int lookahead_pos;
 public void lr_parser();
 public void lr_parser(Scanner);
 public void lr_parser(Scanner, SymbolFactory);
 public SymbolFactory getSymbolFactory();
 protected int error_sync_size();
 public abstract short[][] production_table();
 public abstract short[][] action_table();
 public abstract short[][] reduce_table();
 public abstract int start_state();
 public abstract int start_production();
public abstract int EOF_sym();
 public abstract int error_sym();
 public void done_parsing();
 public void setScanner(Scanner);
 public Scanner getScanner();
 public abstract Symbol do_action(int, lr_parser, java.util.Stack, int) throws Exception;
 public void user_init() throws Exception;
 protected abstract void init_actions() throws Exception;
 public Symbol scan() throws Exception;
 public void report_fatal_error(String, Object) throws Exception;
 public void report_error(String, Object);
 public void syntax_error(Symbol);
 public void unrecovered_syntax_error(Symbol) throws Exception;
 protected final short get_action(int, int);
 protected final short get_reduce(int, int);
 public Symbol parse() throws Exception;
 public void debug_message(String);
 public void dump_stack();
 public void debug_reduce(int, int, int);
 public void debug_shift(Symbol);
 public void debug_stack();
 public Symbol debug_parse() throws Exception;
 protected boolean error_recovery(boolean) throws Exception;
 protected boolean shift_under_error();
 protected boolean find_recovery_config(boolean);
 protected void read_lookahead() throws Exception;
 protected Symbol cur_err_token();
 protected boolean advance_lookahead();
 protected void restart_lookahead() throws Exception;
 protected boolean try_parse_ahead(boolean) throws Exception;
 protected void parse_lookahead(boolean) throws Exception;
 protected static short[][] unpackFromStrings(String[]);
}
java_cup/runtime/virtual_parse_stack.class
package java_cup.runtime;
public synchronized class virtual_parse_stack {
 protected java.util.Stack real_stack;
 protected int real_next;
 protected java.util.Stack vstack;
 public void virtual_parse_stack(java.util.Stack) throws Exception;
 protected void get_from_real();
 public boolean empty();
 public int top() throws Exception;
 public void pop() throws Exception;
 public void push(int);
}
org/bounce/FormConstraints.class
package org.bounce;
public synchronized class FormConstraints {
 public static final int LEFT = 0;
 public static final int BOTTOM = 1;
 public static final int RIGHT = 2;
 public static final int TOP = 3;
 public static final int CENTER = 4;
 public static final int FULL = 5;
 private int position;
 private int horizontalAlignment;
 private int verticalAlignment;
 private boolean filled;
 public void FormConstraints();
 public void FormConstraints(int);
 public void FormConstraints(int, boolean);
 public void FormConstraints(int, int);
 public void FormConstraints(int, int, int);
 public void FormConstraints(FormConstraints);
 public void setFilled(boolean);
 public boolean isFilled();
 public void setHorizontalAlignment(int);
 public int getHorizontalAlignment();
 public void setVerticalAlignment(int);
 public int getVerticalAlignment();
 public void setPosition(int);
 public int getPosition();
 public boolean equals(Object);
}
org/bounce/FormLayout.class
package org.bounce;
public synchronized class FormLayout implements java.awt.LayoutManager2 {
 private static final int MINIMUM = 0;
 private static final int PREFERRED = 1;
 private static final int MAXIMUM = 2;
 public static final FormConstraints LEFT;
 public static final FormConstraints RIGHT;
 public static final FormConstraints RIGHT_FILL;
 public static final FormConstraints FULL;
 public static final FormConstraints FULL_FILL;
 private int horizontalGap;
 private int verticalGap;
 private java.util.HashMap constraints;
 public void FormLayout();
 public void FormLayout(int, int);
 public int getHgap();
 public void setHgap(int);
 public int getVgap();
 public void setVgap(int);
 public void setConstraints(java.awt.Component, Object);
 public void removeLayoutComponent(java.awt.Component);
 public java.awt.Dimension preferredLayoutSize(java.awt.Container);
 public java.awt.Dimension minimumLayoutSize(java.awt.Container);
 public void layoutContainer(java.awt.Container);
 public void addLayoutComponent(java.awt.Component, Object);
 public java.awt.Dimension maximumLayoutSize(java.awt.Container);
 public float getLayoutAlignmentX(java.awt.Container);
 public float getLayoutAlignmentY(java.awt.Container);
 public void invalidateLayout(java.awt.Container);
 public void addLayoutComponent(String, java.awt.Component);
 private int getHeight(int, java.awt.Container);
 private java.awt.Dimension getSize(int, java.awt.Component);
 private java.awt.Dimension getSize(int, java.awt.Container);
 private int getWidth(int, int, java.awt.Container);
 private void align(FormConstraints, java.awt.Rectangle, java.awt.Component);
 static void <clinit>();
}
org/bounce/net/DefaultAuthenticator$1.class
package org.bounce.net;
synchronized class DefaultAuthenticator$1 implements java.awt.event.ActionListener {
 void DefaultAuthenticator$1(DefaultAuthenticator);
 public void actionPerformed(java.awt.event.ActionEvent);
}
org/bounce/net/DefaultAuthenticator$2.class
package org.bounce.net;
synchronized class DefaultAuthenticator$2 implements java.awt.event.ActionListener {
 void DefaultAuthenticator$2(DefaultAuthenticator);
 public void actionPerformed(java.awt.event.ActionEvent);
}
org/bounce/net/DefaultAuthenticator$3.class
package org.bounce.net;
synchronized class DefaultAuthenticator$3 extends java.awt.event.WindowAdapter {
 void DefaultAuthenticator$3(DefaultAuthenticator);
 public void windowClosing(java.awt.event.WindowEvent);
}
org/bounce/net/DefaultAuthenticator.class
package org.bounce.net;
public synchronized class DefaultAuthenticator extends java.net.Authenticator {
 protected String TITLE;
 protected String DESCRIPTION;
 protected String USERNAME;
 protected String PASSWORD;
 protected String HOST;
 protected String REALM;
 protected String OK_BUTTON;
 protected String CANCEL_BUTTON;
 private javax.swing.JDialog dialog;
 private boolean okPressed;
 private javax.swing.JFrame parent;
 private javax.swing.JPasswordField passwordField;
 private javax.swing.JTextField usernameField;
 private javax.swing.JLabel hostField;
 private javax.swing.JLabel realmField;
 public void DefaultAuthenticator(javax.swing.JFrame);
 private javax.swing.JDialog getDialog();
 protected java.net.PasswordAuthentication getPasswordAuthentication();
}
org/pentaho/packageManagement/DefaultPackage.class
package org.pentaho.packageManagement;
public synchronized class DefaultPackage extends Package implements java.io.Serializable {
 private static final long serialVersionUID = 3643121886457892125;
 protected java.io.File m_packageHome;
 protected transient PackageManager m_packageManager;
 public Object clone();
 public void setPackageManager(PackageManager);
 public void DefaultPackage(java.io.File, PackageManager, java.util.Map);
 public void DefaultPackage(java.io.File, PackageManager);
 public java.net.URL getPackageURL() throws Exception;
 public String getName();
 protected static String[] splitNameVersion(String);
 public java.util.List getDependencies() throws Exception;
 public java.util.List getBaseSystemDependency() throws Exception;
 private boolean findPackage(String, java.util.List);
 public java.util.List getMissingDependencies(java.util.List) throws Exception;
 public java.util.List getMissingDependencies() throws Exception;
 public java.util.List getIncompatibleDependencies(java.util.List) throws Exception;
 public java.util.List getIncompatibleDependencies() throws
Exception;
 public boolean isCompatibleBaseSystem() throws Exception;
 public void install() throws Exception;
 public boolean isInstalled();
 public static void main(String[]);
 public void setPackageMetaDataElement(Object, Object) throws Exception;
 public String toString();
}
org/pentaho/packageManagement/DefaultPackageManager.class
package org.pentaho.packageManagement;
public synchronized class DefaultPackageManager extends PackageManager {
 static final int BUFF_SIZE = 100000;
 static final byte[] m_buffer;
 static final String INSTALLED_PACKAGE_CACHE_FILE = installedPackageCache.ser;
 static java.util.List s_installedPackageList;
 public void DefaultPackageManager();
 protected transient java.io.File downloadArchive(java.net.URL, String, java.io.PrintStream[]) throws Exception;
 public Package getURLPackageInfo(java.net.URL) throws Exception;
 public Package getRepositoryPackageInfo(String) throws Exception;
 public java.util.List getRepositoryPackageVersions(String) throws Exception;
 public Package getRepositoryPackageInfo(String, Object) throws Exception;
 private Package getPackageArchiveInfo(java.io.File) throws Exception;
 public Package getPackageArchiveInfo(String) throws Exception;
 public Package getInstalledPackageInfo(String) throws Exception;
 protected boolean establishPackageHome();
 public static transient void deleteDir(java.io.File, java.io.PrintStream[]) throws Exception;
 public transient void uninstallPackage(String, java.io.PrintStream[]) throws Exception;
 public transient String installPackageFromArchive(String, java.io.PrintStream[]) throws Exception;
 protected transient void installAdditionalLibs(String, String[], java.io.PrintStream[]) throws Exception;
 public transient void installPackages(java.util.List, java.io.PrintStream[]) throws Exception;
 protected static boolean checkDependencies(PackageConstraint, java.util.Map, java.util.Map) throws Exception;
 public java.util.List getAllDependenciesForPackage(Package, java.util.Map) throws Exception;
 public transient void installPackageFromRepository(String, Object, java.io.PrintStream[]) throws Exception;
 public transient String installPackageFromURL(java.net.URL, java.io.PrintStream[]) throws Exception;
 private static void copyStreams(java.io.InputStream, java.io.OutputStream) throws java.io.IOException;
 protected transient void installPackage(String, String, java.io.PrintStream[]) throws Exception;
 private java.net.URLConnection getConnection(String) throws java.io.IOException;
 private java.net.URLConnection getConnection(java.net.URL) throws java.io.IOException;
 private void transToBAOS(java.io.BufferedInputStream, java.io.ByteArrayOutputStream) throws Exception;
 private void writeZipEntryForPackage(String, java.util.zip.ZipOutputStream) throws Exception;
 public transient byte[] getRepositoryPackageMetaDataOnlyAsZip(java.io.PrintStream[]) throws Exception;
 public transient byte[] getRepositoryPackageMetaDataOnlyAsZipLegacy(java.io.PrintStream[]) throws Exception;
 public transient java.util.List getAllPackages(java.io.PrintStream[]) throws Exception;
 public java.util.List getAvailablePackages() throws Exception;
 public java.util.List getInstalledPackages() throws Exception;
 protected void deleteInstalledPackageCacheFile() throws Exception;
 protected void saveInstalledPackageCache(java.util.List) throws Exception;
 protected java.util.List loadInstalledPackageCache() throws Exception;
 protected static String padLeft(String, int);
 protected static String padRight(String, int);
 private static String fixStringLength(String, int, boolean);
 public static void main(String[]);
 static void <clinit>();
}
org/pentaho/packageManagement/Dependency.class
package org.pentaho.packageManagement;
public synchronized class Dependency {
 protected Package m_sourcePackage;
 protected PackageConstraint m_targetPackage;
 public void Dependency(Package, PackageConstraint);
 public void setSource(Package);
 public Package getSource();
 public void setTarget(PackageConstraint);
 public PackageConstraint getTarget();
 public String toString();
}
org/pentaho/packageManagement/Package.class
package org.pentaho.packageManagement;
public abstract synchronized class Package implements Cloneable, java.io.Serializable {
 private static final long serialVersionUID = -8193697646938632764;
 protected java.util.Map m_packageMetaData;
 public void Package();
 public void setPackageMetaData(java.util.Map);
 public java.util.Map getPackageMetaData();
 public abstract String getName();
 public abstract java.net.URL getPackageURL() throws Exception;
 public boolean equals(Package);
 public abstract java.util.List getDependencies() throws Exception;
 public abstract boolean isInstalled();
 public abstract void install() throws Exception;
 public abstract boolean isCompatibleBaseSystem() throws Exception;
 public abstract java.util.List getBaseSystemDependency() throws Exception;
 public abstract java.util.List getMissingDependencies() throws Exception;
 public abstract java.util.List getMissingDependencies(java.util.List) throws Exception;
 public abstract java.util.List getIncompatibleDependencies() throws Exception;
 public abstract java.util.List getIncompatibleDependencies(java.util.List) throws Exception;
 public Object getPackageMetaDataElement(Object);
 public abstract void setPackageMetaDataElement(Object, Object) throws Exception;
 public abstract Object clone();
}
org/pentaho/packageManagement/PackageConstraint.class
package org.pentaho.packageManagement;
public abstract synchronized class PackageConstraint {
 protected Package m_thePackage;
 public void PackageConstraint();
 public void setPackage(Package);
 public Package getPackage();
 public abstract boolean checkConstraint(Package) throws Exception;
 public abstract PackageConstraint checkConstraint(PackageConstraint) throws Exception;
}
org/pentaho/packageManagement/PackageManager$1.class
package org.pentaho.packageManagement;
synchronized class PackageManager$1 extends java.net.Authenticator {
 void PackageManager$1(PackageManager);
 protected java.net.PasswordAuthentication getPasswordAuthentication();
}
org/pentaho/packageManagement/PackageManager.class
package org.pentaho.packageManagement;
public abstract synchronized class PackageManager {
 protected java.io.File m_packageHome;
 protected java.net.URL m_packageRepository;
 protected String m_baseSystemName;
 protected Object m_baseSystemVersion;
 protected transient java.net.Proxy m_httpProxy;
 protected transient String m_proxyUsername;
 protected transient String m_proxyPassword;
 protected transient boolean m_authenticatorSet;
 public void PackageManager();
 public static PackageManager create();
 public void establishProxy();
 public synchronized boolean setProxyAuthentication(java.net.URL);
 public void setPackageHome(java.io.File);
 public java.io.File getPackageHome();
 public void setBaseSystemName(String);
 public String getBaseSystemName();
 public void setBaseSystemVersion(Object);
 public Object getBaseSystemVersion();
 public void setPackageRepositoryURL(java.net.URL);
 public java.net.URL getPackageRepositoryURL();
 public void setProxy(java.net.Proxy);
 public java.net.Proxy getProxy();
 public void setProxyUsername(String);
 public void setProxyPassword(String);
 public abstract transient byte[] getRepositoryPackageMetaDataOnlyAsZip(java.io.PrintStream[]) throws Exception;
 public abstract Package getPackageArchiveInfo(String) throws Exception;
public abstract Package getInstalledPackageInfo(String) throws Exception;
 public abstract Package getRepositoryPackageInfo(String) throws Exception;
 public abstract Package getRepositoryPackageInfo(String, Object) throws Exception;
 public abstract java.util.List getRepositoryPackageVersions(String) throws Exception;
 public abstract Package getURLPackageInfo(java.net.URL) throws Exception;
 public abstract transient String installPackageFromArchive(String, java.io.PrintStream[]) throws Exception;
 public abstract transient void installPackageFromRepository(String, Object, java.io.PrintStream[]) throws Exception;
 public abstract transient String installPackageFromURL(java.net.URL, java.io.PrintStream[]) throws Exception;
 public abstract transient void installPackages(java.util.List, java.io.PrintStream[]) throws Exception;
 public abstract transient void uninstallPackage(String, java.io.PrintStream[]) throws Exception;
 public abstract java.util.List getInstalledPackages() throws Exception;
 public abstract transient java.util.List getAllPackages(java.io.PrintStream[]) throws Exception;
 public abstract java.util.List getAvailablePackages() throws Exception;
 public abstract java.util.List getAllDependenciesForPackage(Package, java.util.Map) throws Exception;
}
org/pentaho/packageManagement/VersionPackageConstraint$1.class
package org.pentaho.packageManagement;
synchronized class VersionPackageConstraint$1 {
}
org/pentaho/packageManagement/VersionPackageConstraint$VersionComparison$1.class
package org.pentaho.packageManagement;
final synchronized enum VersionPackageConstraint$VersionComparison$1 {
 void VersionPackageConstraint$VersionComparison$1(String, int, String);
 boolean compatibleWith(VersionPackageConstraint$VersionComparison);
}
org/pentaho/packageManagement/VersionPackageConstraint$VersionComparison$2.class
package org.pentaho.packageManagement;
final synchronized enum VersionPackageConstraint$VersionComparison$2 {
 void VersionPackageConstraint$VersionComparison$2(String, int, String);
 boolean compatibleWith(VersionPackageConstraint$VersionComparison);
}
org/pentaho/packageManagement/VersionPackageConstraint$VersionComparison$3.class
package org.pentaho.packageManagement;
final synchronized enum VersionPackageConstraint$VersionComparison$3 {
 void VersionPackageConstraint$VersionComparison$3(String, int, String);
 boolean compatibleWith(VersionPackageConstraint$VersionComparison);
}
org/pentaho/packageManagement/VersionPackageConstraint$VersionComparison$4.class
package org.pentaho.packageManagement;
final synchronized enum VersionPackageConstraint$VersionComparison$4 {
 void VersionPackageConstraint$VersionComparison$4(String, int, String);
 boolean compatibleWith(VersionPackageConstraint$VersionComparison);
}
org/pentaho/packageManagement/VersionPackageConstraint$VersionComparison$5.class
package org.pentaho.packageManagement;
final synchronized enum VersionPackageConstraint$VersionComparison$5 {
 void VersionPackageConstraint$VersionComparison$5(String, int, String);
 boolean compatibleWith(VersionPackageConstraint$VersionComparison);
}
org/pentaho/packageManagement/VersionPackageConstraint$VersionComparison.class
package org.pentaho.packageManagement;
public abstract synchronized enum VersionPackageConstraint$VersionComparison {
 public static final VersionPackageConstraint$VersionComparison EQUAL;
 public static final VersionPackageConstraint$VersionComparison GREATERTHAN;
 public static final VersionPackageConstraint$VersionComparison GREATERTHANOREQUAL;
 public static final VersionPackageConstraint$VersionComparison LESSTHAN;
 public static final VersionPackageConstraint$VersionComparison LESSTHANOREQUAL;
 private final String m_stringVal;
 public static VersionPackageConstraint$VersionComparison[] values();
 public static VersionPackageConstraint$VersionComparison valueOf(String);
 private void VersionPackageConstraint$VersionComparison(String, int, String);
 abstract boolean compatibleWith(VersionPackageConstraint$VersionComparison);
 public String toString();
 static void <clinit>();
}
org/pentaho/packageManagement/VersionPackageConstraint.class
package org.pentaho.packageManagement;
public synchronized class VersionPackageConstraint extends PackageConstraint {
 public static String VERSION_KEY;
 protected VersionPackageConstraint$VersionComparison m_constraint;
 protected static VersionPackageConstraint$VersionComparison getVersionComparison(String);
 protected static int[] parseVersion(String);
 protected static boolean checkConstraint(String, VersionPackageConstraint$VersionComparison, String);
 protected static VersionPackageConstraint$VersionComparison compare(String, String);
 public void VersionPackageConstraint(Package);
 public void setVersionConstraint(VersionPackageConstraint$VersionComparison);
 public VersionPackageConstraint$VersionComparison getVersionComparison();
 public void setVersionConstraint(String);
 public PackageConstraint checkConstraint(PackageConstraint) throws Exception;
 public boolean checkConstraint(Package) throws Exception;
 public String toString();
 static void <clinit>();
}
org/pentaho/packageManagement/VersionRangePackageConstraint.class
package org.pentaho.packageManagement;
public synchronized class VersionRangePackageConstraint extends PackageConstraint {
 protected String m_lowerBound;
 protected VersionPackageConstraint$VersionComparison m_lowerConstraint;
 protected String m_upperBound;
 protected VersionPackageConstraint$VersionComparison m_upperConstraint;
 protected boolean m_boundOr;
 public void VersionRangePackageConstraint(Package);
 public void setRangeConstraint(String, VersionPackageConstraint$VersionComparison, String, VersionPackageConstraint$VersionComparison) throws Exception;
 public String getLowerBound();
 public String getUpperBound();
 public VersionPackageConstraint$VersionComparison getLowerComparison();
 public VersionPackageConstraint$VersionComparison getUpperComparison();
 public boolean isBoundOR();
 protected static boolean checkConstraint(String, VersionPackageConstraint$VersionComparison, String, VersionPackageConstraint$VersionComparison, String, boolean);
 public boolean checkConstraint(Package) throws Exception;
 protected PackageConstraint checkTargetVersionRangePackageConstraint(VersionRangePackageConstraint) throws Exception;
 protected PackageConstraint checkTargetVersionPackageConstraint(VersionPackageConstraint) throws Exception;
 public PackageConstraint checkConstraint(PackageConstraint) throws Exception;
}
weka/Run$SchemeType.class
package weka;
public final synchronized enum Run$SchemeType {
 public static final Run$SchemeType CLASSIFIER;
 public static final Run$SchemeType CLUSTERER;
 public static final Run$SchemeType ASSOCIATOR;
 public static final Run$SchemeType ATTRIBUTE_SELECTION;
 public static final Run$SchemeType FILTER;
 public static final Run$SchemeType LOADER;
 public static final Run$SchemeType SAVER;
 public static final Run$SchemeType DATAGENERATOR;
 public static final Run$SchemeType COMMANDLINE;
 private final String m_stringVal;
 public static Run$SchemeType[] values();
 public static Run$SchemeType valueOf(String);
 private void Run$SchemeType(String, int, String);
 public String toString();
 static void <clinit>();
}
weka/Run.class
package weka;
public synchronized class Run {
 public void Run();
 public static java.util.List findSchemeMatch(Class, String, boolean, boolean);
 public static java.util.List findSchemeMatch(String,
boolean);
 public static void main(String[]);
}
weka/associations/AbstractAssociator.class
package weka.associations;
public abstract synchronized class AbstractAssociator implements Cloneable, Associator, java.io.Serializable, weka.core.CapabilitiesHandler, weka.core.RevisionHandler {
 private static final long serialVersionUID = -3017644543382432070;
 public void AbstractAssociator();
 public static Associator forName(String, String[]) throws Exception;
 public static Associator makeCopy(Associator) throws Exception;
 public static Associator[] makeCopies(Associator, int) throws Exception;
 public weka.core.Capabilities getCapabilities();
 public String getRevision();
 public static void runAssociator(Associator, String[]);
}
weka/associations/Apriori.class
package weka.associations;
public synchronized class Apriori extends AbstractAssociator implements weka.core.OptionHandler, AssociationRulesProducer, CARuleMiner, weka.core.TechnicalInformationHandler {
 static final long serialVersionUID = 3277498842319212687;
 protected double m_minSupport;
 protected double m_upperBoundMinSupport;
 protected double m_lowerBoundMinSupport;
 protected static final int CONFIDENCE = 0;
 protected static final int LIFT = 1;
 protected static final int LEVERAGE = 2;
 protected static final int CONVICTION = 3;
 public static final weka.core.Tag[] TAGS_SELECTION;
 protected int m_metricType;
 protected double m_minMetric;
 protected int m_numRules;
 protected double m_delta;
 protected double m_significanceLevel;
 protected int m_cycles;
 protected java.util.ArrayList m_Ls;
 protected java.util.ArrayList m_hashtables;
 protected java.util.ArrayList[] m_allTheRules;
 protected weka.core.Instances m_instances;
 protected boolean m_outputItemSets;
 protected boolean m_removeMissingCols;
 protected boolean m_verbose;
 protected weka.core.Instances m_onlyClass;
 protected int m_classIndex;
 protected boolean m_car;
 protected boolean m_treatZeroAsMissing;
 protected String m_toStringDelimiters;
 public String globalInfo();
 public weka.core.TechnicalInformation getTechnicalInformation();
 public void Apriori();
 public void resetOptions();
 protected weka.core.Instances removeMissingColumns(weka.core.Instances) throws Exception;
 public weka.core.Capabilities getCapabilities();
 public void buildAssociations(weka.core.Instances) throws Exception;
 private void pruneRulesForUpperBoundSupport();
 public java.util.ArrayList[] mineCARs(weka.core.Instances) throws Exception;
 public weka.core.Instances getInstancesNoClass();
 public weka.core.Instances getInstancesOnlyClass();
 public java.util.Enumeration listOptions();
 public void setOptions(String[]) throws Exception;
 public String[] getOptions();
 public String toString();
 public String metricString();
 public String removeAllMissingColsTipText();
 public void setRemoveAllMissingCols(boolean);
 public boolean getRemoveAllMissingCols();
 public String upperBoundMinSupportTipText();
 public double getUpperBoundMinSupport();
 public void setUpperBoundMinSupport(double);
 public void setClassIndex(int);
 public int getClassIndex();
 public String classIndexTipText();
 public void setCar(boolean);
 public boolean getCar();
 public String carTipText();
 public String lowerBoundMinSupportTipText();
 public double getLowerBoundMinSupport();
 public void setLowerBoundMinSupport(double);
 public weka.core.SelectedTag getMetricType();
 public String metricTypeTipText();
 public void setMetricType(weka.core.SelectedTag);
 public String minMetricTipText();
 public double getMinMetric();
 public void setMinMetric(double);
 public String numRulesTipText();
 public int getNumRules();
 public void setNumRules(int);
 public String deltaTipText();
 public double getDelta();
 public void setDelta(double);
 public String significanceLevelTipText();
 public double getSignificanceLevel();
 public void setSignificanceLevel(double);
 public void setOutputItemSets(boolean);
 public boolean getOutputItemSets();
 public String outputItemSetsTipText();
 public void setVerbose(boolean);
 public boolean getVerbose();
 public String verboseTipText();
 public String treatZeroAsMissingTipText();
 public void setTreatZeroAsMissing(boolean);
 public boolean getTreatZeroAsMissing();
 private void findLargeItemSets() throws Exception;
 private void findRulesBruteForce() throws Exception;
 private void findRulesQuickly() throws Exception;
 private void findLargeCarItemSets() throws Exception;
 private void findCarRulesQuickly() throws Exception;
 public java.util.ArrayList[] getAllTheRules();
 public AssociationRules getAssociationRules();
 public String[] getRuleMetricNames();
 public boolean canProduceRules();
 public String getRevision();
 public static void main(String[]);
 static void <clinit>();
}
weka/associations/AprioriItemSet.class
package weka.associations;
public synchronized class AprioriItemSet extends ItemSet implements java.io.Serializable, weka.core.RevisionHandler {
 static final long serialVersionUID = 7684467755712672058;
 public void AprioriItemSet(int);
 public static double confidenceForRule(AprioriItemSet, AprioriItemSet);
 public double liftForRule(AprioriItemSet, AprioriItemSet, int);
 public double leverageForRule(AprioriItemSet, AprioriItemSet, int, int);
 public double convictionForRule(AprioriItemSet, AprioriItemSet, int, int);
 public java.util.ArrayList[] generateRules(double, java.util.ArrayList, int);
 public final java.util.ArrayList[] generateRulesBruteForce(double, int, java.util.ArrayList, int, int, double) throws Exception;
 public final AprioriItemSet subtract(AprioriItemSet);
 private final java.util.ArrayList[] moreComplexRules(java.util.ArrayList[], int, int, double, java.util.ArrayList);
 public final String toString(weka.core.Instances);
 public static java.util.ArrayList singletons(weka.core.Instances, boolean) throws Exception;
 public static java.util.ArrayList mergeAllItemSets(java.util.ArrayList, int, int);
 public String getRevision();
}
weka/associations/AssociationRule.class
package weka.associations;
public abstract synchronized class AssociationRule implements Comparable {
 public void AssociationRule();
 public abstract java.util.Collection getPremise();
 public abstract java.util.Collection getConsequence();
 public abstract String getPrimaryMetricName();
 public abstract double getPrimaryMetricValue();
 public abstract double getNamedMetricValue(String) throws Exception;
 public abstract int getNumberOfMetricsForRule();
 public abstract String[] getMetricNamesForRule();
 public abstract double[] getMetricValuesForRule() throws Exception;
 public abstract int getPremiseSupport();
 public abstract int getConsequenceSupport();
 public abstract int getTotalSupport();
 public abstract int getTotalTransactions();
 public int compareTo(AssociationRule);
 public boolean equals(Object);
 public boolean containsItems(java.util.ArrayList, boolean);
}
weka/associations/AssociationRules.class
package weka.associations;
public synchronized class AssociationRules implements java.io.Serializable {
 private static final long serialVersionUID = 8889198755948056749;
 protected String m_producer;
 protected java.util.List m_rules;
 public void AssociationRules(java.util.List, String);
 public void AssociationRules(java.util.List, Object);
 public void AssociationRules(java.util.List);
 public void setRules(java.util.List);
public java.util.List getRules();
 public int getNumRules();
 public void setProducer(String);
 public String getProducer();
}
weka/associations/AssociationRulesProducer.class
package weka.associations;
public abstract interface AssociationRulesProducer {
 public abstract AssociationRules getAssociationRules();
 public abstract String[] getRuleMetricNames();
 public abstract boolean canProduceRules();
}
weka/associations/Associator.class
package weka.associations;
public abstract interface Associator {
 public abstract void buildAssociations(weka.core.Instances) throws Exception;
 public abstract weka.core.Capabilities getCapabilities();
}
weka/associations/AssociatorEvaluation.class
package weka.associations;
public synchronized class AssociatorEvaluation implements weka.core.RevisionHandler {
 protected StringBuffer m_Result;
 public void AssociatorEvaluation();
 protected static String makeOptionString(Associator);
 public static String evaluate(String, String[]) throws Exception;
 public static String evaluate(Associator, String[]) throws Exception;
 public String evaluate(Associator, weka.core.Instances) throws Exception;
 public boolean equals(Object);
 public String toSummaryString();
 public String toSummaryString(String);
 public String toString();
 public String getRevision();
 public static void main(String[]);
}
weka/associations/BinaryItem.class
package weka.associations;
public synchronized class BinaryItem extends NominalItem implements java.io.Serializable {
 private static final long serialVersionUID = -3372941834914147669;
 public void BinaryItem(weka.core.Attribute, int) throws Exception;
 public boolean equals(Object);
 public int hashCode();
}
weka/associations/CARuleMiner.class
package weka.associations;
public abstract interface CARuleMiner extends weka.core.OptionHandler {
 public abstract java.util.ArrayList[] mineCARs(weka.core.Instances) throws Exception;
 public abstract weka.core.Instances getInstancesNoClass();
 public abstract weka.core.Instances getInstancesOnlyClass();
 public abstract String metricString();
 public abstract void setClassIndex(int);
}
weka/associations/CheckAssociator.class
package weka.associations;
public synchronized class CheckAssociator extends weka.core.CheckScheme implements weka.core.RevisionHandler {
 public static final int NO_CLASS = -1;
 protected Associator m_Associator;
 public void CheckAssociator();
 public java.util.Enumeration listOptions();
 public void setOptions(String[]) throws Exception;
 public String[] getOptions();
 public void doTests();
 public void setAssociator(Associator);
 public Associator getAssociator();
 protected void testsPerClassType(int, boolean, boolean);
 protected void testsWithoutClass(boolean, boolean);
 protected boolean[] canTakeOptions();
 protected boolean[] weightedInstancesHandler();
 protected boolean[] multiInstanceHandler();
 protected boolean[] declaresSerialVersionUID();
 protected boolean[] canPredict(boolean, boolean, boolean, boolean, boolean, boolean, int);
 protected boolean[] canHandleNClasses(boolean, boolean, boolean, boolean, boolean, boolean, int);
 protected boolean[] canHandleClassAsNthAttribute(boolean, boolean, boolean, boolean, boolean, boolean, int, int);
 protected boolean[] canHandleZeroTraining(boolean, boolean, boolean, boolean, boolean, boolean, int);
 protected boolean[] correctBuildInitialisation(boolean, boolean, boolean, boolean, boolean, boolean, int);
 protected boolean[] canHandleMissing(boolean, boolean, boolean, boolean, boolean, boolean, int, boolean, boolean, int);
 protected boolean[] instanceWeights(boolean, boolean, boolean, boolean, boolean, boolean, int);
 protected boolean[] datasetIntegrity(boolean, boolean, boolean, boolean, boolean, boolean, int, boolean, boolean);
 protected boolean[] runBasicTest(boolean, boolean, boolean, boolean, boolean, boolean, int, int, boolean, boolean, int, int, java.util.ArrayList);
 protected boolean[] runBasicTest(boolean, boolean, boolean, boolean, boolean, boolean, int, int, int, boolean, boolean, int, int, java.util.ArrayList);
 protected weka.core.Instances makeTestDataset(int, int, int, int, int, int, int, int, int, boolean) throws Exception;
 protected weka.core.Instances makeTestDataset(int, int, int, int, int, int, int, int, int, int, boolean) throws Exception;
 protected void printAttributeSummary(boolean, boolean, boolean, boolean, boolean, boolean, int);
 public String getRevision();
 public static void main(String[]);
}
weka/associations/DefaultAssociationRule$1.class
package weka.associations;
synchronized class DefaultAssociationRule$1 {
}
weka/associations/DefaultAssociationRule$METRIC_TYPE$1.class
package weka.associations;
final synchronized enum DefaultAssociationRule$METRIC_TYPE$1 {
 void DefaultAssociationRule$METRIC_TYPE$1(String, int, String);
 double compute(int, int, int, int);
}
weka/associations/DefaultAssociationRule$METRIC_TYPE$2.class
package weka.associations;
final synchronized enum DefaultAssociationRule$METRIC_TYPE$2 {
 void DefaultAssociationRule$METRIC_TYPE$2(String, int, String);
 double compute(int, int, int, int);
}
weka/associations/DefaultAssociationRule$METRIC_TYPE$3.class
package weka.associations;
final synchronized enum DefaultAssociationRule$METRIC_TYPE$3 {
 void DefaultAssociationRule$METRIC_TYPE$3(String, int, String);
 double compute(int, int, int, int);
}
weka/associations/DefaultAssociationRule$METRIC_TYPE$4.class
package weka.associations;
final synchronized enum DefaultAssociationRule$METRIC_TYPE$4 {
 void DefaultAssociationRule$METRIC_TYPE$4(String, int, String);
 double compute(int, int, int, int);
}
weka/associations/DefaultAssociationRule$METRIC_TYPE.class
package weka.associations;
public abstract synchronized enum DefaultAssociationRule$METRIC_TYPE {
 public static final DefaultAssociationRule$METRIC_TYPE CONFIDENCE;
 public static final DefaultAssociationRule$METRIC_TYPE LIFT;
 public static final DefaultAssociationRule$METRIC_TYPE LEVERAGE;
 public static final DefaultAssociationRule$METRIC_TYPE CONVICTION;
 private final String m_stringVal;
 public static DefaultAssociationRule$METRIC_TYPE[] values();
 public static DefaultAssociationRule$METRIC_TYPE valueOf(String);
 private void DefaultAssociationRule$METRIC_TYPE(String, int, String);
 abstract double compute(int, int, int, int);
 public String toString();
 public String toStringMetric(int, int, int, int);
 public String toXML(int, int, int, int);
 static void <clinit>();
}
weka/associations/DefaultAssociationRule.class
package weka.associations;
public synchronized class DefaultAssociationRule extends AssociationRule implements java.io.Serializable {
 private static final long serialVersionUID = -661269018702294489;
 public static final weka.core.Tag[] TAGS_SELECTION;
 protected DefaultAssociationRule$METRIC_TYPE m_metricType;
 protected java.util.Collection m_premise;
 protected java.util.Collection m_consequence;
 protected int m_premiseSupport;
 protected int m_consequenceSupport;
 protected int m_totalSupport;
 protected int m_totalTransactions;
 public void DefaultAssociationRule(java.util.Collection, java.util.Collection, DefaultAssociationRule$METRIC_TYPE, int, int, int, int);
 public java.util.Collection getPremise();
 public java.util.Collection getConsequence();
 public String getPrimaryMetricName();
 public double getPrimaryMetricValue();
 public double getNamedMetricValue(String)
throws Exception;
 public int getNumberOfMetricsForRule();
 public String[] getMetricNamesForRule();
 public double[] getMetricValuesForRule() throws Exception;
 public int getPremiseSupport();
 public int getConsequenceSupport();
 public int getTotalSupport();
 public int getTotalTransactions();
 public String toString();
 static void <clinit>();
}
weka/associations/FPGrowth$FPTreeNode.class
package weka.associations;
public synchronized class FPGrowth$FPTreeNode implements java.io.Serializable {
 private static final long serialVersionUID = 4396315323673737660;
 protected FPGrowth$FPTreeNode m_levelSibling;
 protected FPGrowth$FPTreeNode m_parent;
 protected BinaryItem m_item;
 protected int m_ID;
 protected java.util.Map m_children;
 protected FPGrowth$ShadowCounts m_projectedCounts;
 public void FPGrowth$FPTreeNode(FPGrowth$FPTreeNode, BinaryItem);
 public void addItemSet(java.util.Collection, java.util.Map, int);
 public void increaseProjectedCount(int, int);
 public void removeProjectedCount(int);
 public int getProjectedCount(int);
 public FPGrowth$FPTreeNode getParent();
 public BinaryItem getItem();
 public String toString(int);
 public String toString(String, int);
 protected int assignIDs(int);
 public void graphFPTree(StringBuffer);
}
weka/associations/FPGrowth$FPTreeRoot$Header.class
package weka.associations;
public synchronized class FPGrowth$FPTreeRoot$Header implements java.io.Serializable {
 private static final long serialVersionUID = -6583156284891368909;
 protected java.util.List m_headerList;
 protected FPGrowth$ShadowCounts m_projectedHeaderCounts;
 protected void FPGrowth$FPTreeRoot$Header();
 public void addToList(FPGrowth$FPTreeNode);
 public java.util.List getHeaderList();
 public FPGrowth$ShadowCounts getProjectedCounts();
}
weka/associations/FPGrowth$FPTreeRoot.class
package weka.associations;
synchronized class FPGrowth$FPTreeRoot extends FPGrowth$FPTreeNode {
 private static final long serialVersionUID = 632150939785333297;
 protected java.util.Map m_headerTable;
 public void FPGrowth$FPTreeRoot();
 public void addItemSet(java.util.Collection, int);
 public java.util.Map getHeaderTable();
 public boolean isEmpty(int);
 public String toString(String, int);
}
weka/associations/FPGrowth$FrequentBinaryItemSet.class
package weka.associations;
public synchronized class FPGrowth$FrequentBinaryItemSet implements java.io.Serializable, Cloneable {
 private static final long serialVersionUID = -6543815873565829448;
 protected java.util.ArrayList m_items;
 protected int m_support;
 public void FPGrowth$FrequentBinaryItemSet(java.util.ArrayList, int);
 public void addItem(BinaryItem);
 public void setSupport(int);
 public int getSupport();
 public java.util.Collection getItems();
 public BinaryItem getItem(int);
 public int numberOfItems();
 public String toString();
 public Object clone();
}
weka/associations/FPGrowth$FrequentItemSets$1.class
package weka.associations;
synchronized class FPGrowth$FrequentItemSets$1 implements java.util.Comparator {
 void FPGrowth$FrequentItemSets$1(FPGrowth$FrequentItemSets);
 public int compare(FPGrowth$FrequentBinaryItemSet, FPGrowth$FrequentBinaryItemSet);
}
weka/associations/FPGrowth$FrequentItemSets.class
package weka.associations;
public synchronized class FPGrowth$FrequentItemSets implements java.io.Serializable {
 private static final long serialVersionUID = 4173606872363973588;
 protected java.util.ArrayList m_sets;
 protected int m_numberOfTransactions;
 public void FPGrowth$FrequentItemSets(int);
 public FPGrowth$FrequentBinaryItemSet getItemSet(int);
 public java.util.Iterator iterator();
 public int getNumberOfTransactions();
 public void addItemSet(FPGrowth$FrequentBinaryItemSet);
 public void sort(java.util.Comparator);
 public int size();
 public void sort();
 public String toString(int);
}
weka/associations/FPGrowth$ShadowCounts.class
package weka.associations;
public synchronized class FPGrowth$ShadowCounts implements java.io.Serializable {
 private static final long serialVersionUID = 4435433714185969155;
 private final java.util.ArrayList m_counts;
 protected void FPGrowth$ShadowCounts();
 public int getCount(int);
 public void increaseCount(int, int);
 public void removeCount(int);
}
weka/associations/FPGrowth.class
package weka.associations;
public synchronized class FPGrowth extends AbstractAssociator implements AssociationRulesProducer, weka.core.OptionHandler, weka.core.TechnicalInformationHandler {
 private static final long serialVersionUID = 3620717108603442911;
 protected int m_numRulesToFind;
 protected double m_upperBoundMinSupport;
 protected double m_lowerBoundMinSupport;
 protected double m_delta;
 protected int m_numInstances;
 protected int m_offDiskReportingFrequency;
 protected boolean m_findAllRulesForSupportLevel;
 protected int m_positiveIndex;
 protected DefaultAssociationRule$METRIC_TYPE m_metric;
 protected double m_metricThreshold;
 protected FPGrowth$FrequentItemSets m_largeItemSets;
 protected java.util.List m_rules;
 protected int m_maxItems;
 protected String m_transactionsMustContain;
 protected boolean m_mustContainOR;
 protected String m_rulesMustContain;
 private static void nextSubset(boolean[]);
 private static java.util.Collection getPremise(FPGrowth$FrequentBinaryItemSet, boolean[]);
 private static java.util.Collection getConsequence(FPGrowth$FrequentBinaryItemSet, boolean[]);
 public static java.util.List generateRulesBruteForce(FPGrowth$FrequentItemSets, DefaultAssociationRule$METRIC_TYPE, double, int, int, int);
 public static java.util.List pruneRules(java.util.List, java.util.ArrayList, boolean);
 public weka.core.Capabilities getCapabilities();
 public String globalInfo();
 public weka.core.TechnicalInformation getTechnicalInformation();
 private boolean passesMustContain(weka.core.Instance, boolean[], int);
 private void processSingleton(weka.core.Instance, java.util.ArrayList) throws Exception;
 protected java.util.ArrayList getSingletons(Object) throws Exception;
 protected java.util.ArrayList getSingletons(weka.core.Instances) throws Exception;
 private void insertInstance(weka.core.Instance, java.util.ArrayList, FPGrowth$FPTreeRoot, int);
 protected FPGrowth$FPTreeRoot buildFPTree(java.util.ArrayList, Object, int) throws Exception;
 protected void mineTree(FPGrowth$FPTreeRoot, FPGrowth$FrequentItemSets, int, FPGrowth$FrequentBinaryItemSet, int);
 public void FPGrowth();
 public void resetOptions();
 public String positiveIndexTipText();
 public void setPositiveIndex(int);
 public int getPositiveIndex();
 public void setNumRulesToFind(int);
 public int getNumRulesToFind();
 public String numRulesToFindTipText();
 public void setMetricType(weka.core.SelectedTag);
 public void setMaxNumberOfItems(int);
 public int getMaxNumberOfItems();
 public String maxNumberOfItemsTipText();
 public weka.core.SelectedTag getMetricType();
 public String metricTypeTipText();
 public String minMetricTipText();
 public double getMinMetric();
 public void setMinMetric(double);
 public String transactionsMustContainTipText();
 public void setTransactionsMustContain(String);
 public String getTransactionsMustContain();
 public String rulesMustContainTipText();
 public void setRulesMustContain(String);
 public String getRulesMustContain();
 public String useORForMustContainListTipText();
 public void setUseORForMustContainList(boolean);