$.$ Determine whether the following statements are true or false. Write $$T$$ for true and $$F$$ for false. $8$

i$)$ Apriori principle is useful in pruning infrequent itemsets without explicitly counting their support by scanning the database.

Answer:

ii$)$ In k$-$means clustering, the number of the final clusters is $2$k$.$

Answer:

iii$)$ In partitional clustering, a point can belong to multiple clusters.

Answer:

iv$)$ Like classification, cluster analysis is a supervised learning.

Answer:

v$)$ Simple segmentation is not cluster analysis.

Answer:

vi$)$ Lowering the support threshold will increase the runtime of the Apriori algorithm for finding the frequent itemsets.

Answer:

vii$)$ Some center$-$based clusters can also be well$-$separated clusters.

Answer:

viii$)$ Rule$-$based classifiers is as expressive as decision trees.

Answer: