In hierarchical clustering with complete linkage clustering, we should group two clusters with the max distance to be a new group.

True False

Agglomerative hierarchical clustering starts with single elements and aggregates them into clusters.

True False

$K-$means is a centroid clustering algorithm to find a tocal optimum. Its process has to be repeated until finding a constant value for centroids.

True False

The elbow, average silhouette, and gap statistic methods can be used to determine the amount of optimal clusters. They must obtain the same optimal result.

True False

In Association Rule Discovery, "Support" metric indicates how often the association rule can be applied.

True False

In $R$ language, dist$()$ function is required to calculate distance between elements before holust$()$ function.

True False

K$-$manes is an optimization problem which can be solved in polynomial time.

True False

In $R$ language, datasets should be converted to transactional format before calling apriorio function to find rules.

True False

In $R$ language, minlen is used to limit the minimum amount of left$-$hand$-$side items.

True False

Hive queries work like the traditional SQL queries, that invoke database events.

True False