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

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False

$2.$ Agglomerative hierarchical elustering starts with single elements and aggregates them into elusters.

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False

$3.$ K$-$means is a centroid clustering algorithm to find a local optimum. Its process has to be repeated until finding a constant value for centroids.

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False

$4.$ 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.

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False

$5.$ In Association Rule Discovery, "Support" metric indicates how often the association rule can be applied.

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False

$6.$ In R language, distO function is required to calculate distance between elements before hclust function.

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False

$7.$ K$-$manes is an optimization problem which can be solved in polynomial time.

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False

$8.$ In R language, datasets should be converted to transactional format before calling apriori function to find rules.

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False

$9.$ In R language, minlen is used to limit the minimum amount of left$-$hand$-$side items.

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$10.$ Hive queries work like the traditional SQL queries, that invoke database events.

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