Ivy_Honeywell_Data Analytics_6.1

Point out the correct statement:

• The choice of an appropriate metric will influence the shape of the clusters

• Hierarchical clustering is also called HCA

• In general, the merges and splits are determined in a greedy manner

• All of the mentioned

Which of the following is finally produced by Hierarchical Clustering?

• Final estimate of cluster centroids

• Tree showing how close things are to each other

• Assignment of each point to clusters

• All of the mentioned

Which of the following is required by K-means clustering?

• Defined distance metric

• Number of clusters

• Initial guess as to cluster centroids

• All of the mentioned

Point out the wrong statement:

• K-means clustering is a method of vector quantisation

• K-means clustering aims to partition n observations into k clusters

• K-nearest neighbour is same as K-means

• None of the mentioned

Which of the following combination is incorrect?

• Continuous-euclidean distance

• Continuous-correlation similarity

• Binary-manhattan distance

• None of the mentioned

Hierarchical clustering should be primarily used for exploration.

• TRUE

• FALSE

K-means is not deterministic and it also consists of number of iterations.

• TRUE

• FALSE

Which of the following clustering requires merging approach?

• Partitional

• Hierarchical

• Naïve Bayes

• None of the mentioned

Which of the following function is used for k-means clustering?

• k-means

• k-mean

• heatmap

• None of the above

Can decision trees be used for clustering?

• TRUE

• FALSE