After forming groups of observations from a data set (sample) using a clustering algorithm, we can name each group and classify each individual wit...

After forming groups of observations from a data set (sample) using a clustering algorithm, we can name each group and classify each individual within the group. Humans do this naturally, first grouping and then naming the groups. For example, vertebrate or invertebrate animals, cars or airplanes, men or women.

Based on the above, analyze the following assertions and the proposed relationship between them and choose the correct alternative:

I. After forming and naming (classifying) the groups of observations resulting from the algorithm, it is not possible to use these classes as response variables and perform predictive tasks with classification algorithms.
Because
II. Clustering algorithms are part of the methods of so-called unsupervised learning. They are not predictive models.


a. Assertion I and II are false propositions.
b. Assertion I is a true proposition and assertion II is a false proposition.
c. Assertion I is a false proposition, and assertion II is a true proposition.
d. Assertion I and II are true propositions, but II is not a justification for I.
e. Assertion I and II are true propositions, and II is a correct justification for I.