A and D

None of the graphs show positive correlation between x1 and x2

A and C

B and C

A and B

A

B

We do not choose too many clusters:

Although hierarchical clustering gives a solution for any number of

clusters, ultimately we only want to focus on one of these solutions.

There is no correct number of clusters. Choosing the number of

clusters depends on the context.

TF-IDF measures the similarity between documents by comparing the term frequency of words in each document to the average frequency across the corpus, without considering document length or term distribution.

TF-IDF measures a word's importance within a document relative to a collection or corpus, adjusting for the fact that some words occur more frequently across all documents.

TF-IDF calculates the frequency of each term in a document and multiplies it by the number of documents containing that term, to evaluate how relevant a term is to the document.

TF-IDF assigns a weight to each term based on its occurrence in a document and the total number of words in the document, normalizing the importance of terms within the document.