clus

In the K-Means algorithm, we have to specify the number of clusters.

• 
  

• • True

• • False

What metric can be used to find an optimal number of clusters ?

• • R Squared

• • MSE

• • WCSS

We can choose any random initial centroids at the beginning of K-Means.

• • True

• • False

What is step 1 in K-Means?

• • Choose the number of Decision Trees

• • Choose the number of K of clusters

• • Remove all K clusters

• • None of the above

Is the following true?

For step 4 we have to:

1. Compute and place the new centroid of each cluster?

• • True

• • False

What can we use in Hierarchical Clustering to find the right number of clusters ?

• • The Elbow Method

• • Decision Trees

• • Dendrograms

• • Histograms

The goal of clustering a set of data is to

• divide them into groups of data that are near each other

• choose the best data from the set

• determine the nearest neighbors of each of the data

• predict the class of data

In the figure above, if you draw a horizontal line on y-axis for y=2. What will be the number of clusters formed?

• 2

• 4

• 3

• 5

Clustering is the type of

• Supervised Learning

• Unsupervised Learning

Which distance measure is used by K-means clustering algorithm?

• Hamming Distance

• Euclidean Distance

• Manhattan Distance

• Minkowski Distance