KMeans & AHC

The problem of finding hidden structure in unlabelled data is called _______.

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• None of the mentioned

Which of the following algorithm is most sensitive to outliers?

• k-means clustering algorithm

• k-medians clustering algorithm

• k-modes clustering algorithm

• k-medoids clustering algorithm

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

• Defined distance metric

• Number of clusters

• Initial guess as to cluster centroids

• All the mentioned

WCSS stands for

• with cluster sum of squares

• within cluster sum of squares

• within cluster sum of standards

• None of the mentioned

kMeans model is present in the _______ class of sklearn library

• models

• linear

• cluster

• None of the mentioned

The keyword that returns the wcss values is

• interia_

• wcss_

• init_

• None of the mentioned

The optimum number of clusters in kMeans algorithm is found out using

• Dendrogram

• Elbow method

• Segregation

• None of the mentioned

The problem of bad initialization of centrodis lead to _______

• Cluster error

• Recurssive cluster

• Uneven cluster

• Random Initialization trap

RIT can be overcome using _______

• kmedoids

• kmeans++

• kmodes

• None of the mentioned

Agglomerative hierarchical clustering model is present in the _______ class of sklearn library

• models

• linear

• cluster

• None of the mentioned