What is a preferred distance measure while dealing with sets ?
Jaccard — Correct
Each point is a cluster in itself. We then combine the two nearest clusters into one. What type of clustering does this represent ?
Agglomerative — Correct
Which learning is the method of finding structure in the data without labels.
Unsupervised — Correct
__ of a set of points is defined using a distance measure .
Similarity — Correct
Members of the same cluster are far away / distant from each other .
False — Correct
Unsupervised learning focuses on understanding the data and its underlying pattern.
True — Correct
_ of two points is the average of the two points in Eucledian Space.
Centroid — Correct
A centroid is a valid point in a non-Eucledian space .
False — Correct
What is the overall complexity of the the Agglomerative Hierarchical Clustering ?
O(N^3) — Correct
_ measures the goodness of a cluster
Cohesion — Correct
_ is the data point that is closest to the other point in the cluster.
Clusteroid — Correct
The __ is a visual representation of how the data points are merged to form clusters.
Dendogram — Correct
_ is when points don’t move between clusters and centroids stabilize.
Convergence — Correct
_ is a way of finding the k value for k means clustering.
Cross Validation — Correct
The number of rounds for convergence in k means clustering can be lage
True — Correct
Sampling is one technique to pick the initial k points in K Means Clustering
True — Correct
K Means algorithm assumes Eucledian Space/Distance
True — Correct
What is the R Function to divide a dataset into k clusters ?
kclusters() — Wrong
What is the R function to apply hierarchical clustering to a matrix of distance objects ?
hclust() — Correct
Hierarchical Clustering is a suggested approach for Large Data Sets – False
What is the R Function to divide a dataset into k clusters ?
KMeans is the correct answer