Clustering the Data Ensemble | Fresco Play

Question 1: Members of the same cluster are far away / distant from each other .

Answer: False

Question 2: unsupervised learning focuses on understanding the data and its underlying pattern.

Answer: True

Question 3: Each point is a cluster in itself. We then combine the two nearest clusters into one. What type of clustering does this represent ?

Answer: Agglomerative

Question 4: What is a preferred distance measure while dealing with sets ?

Answer: Jaccard

Question 5: Which learning is the method of finding structure in the data without labels.

Answer: Unsupervised

Question 6: __________ measures the goodness of a cluster

Answer: Cohesion

Question 7: A centroid is a valid point in a non-Eucledian space .

Answer: False

Question 8: ___________ of two points is the average of the two points in Eucledian Space.

Answer: Centroid

Question 9: The ______ is a visual representation of how the data points are merged to form clusters.

Answer: Dendogram

Question 10: ___________ is the data point that is closest to the other point in the cluster.

Answer: Clusteroid

Question 11: Sampling is one technique to pick the initial k points in K Means Clustering

Answer: True

Question 12: The number of rounds for convergence in k means clustering can be lage

Answer: True

Question 13: Hierarchical Clustering is a suggested approach for Large Data Sets

Answer: False

Question 14: __________ is a way of finding the k value for k means clustering.

Answer: Cross

Question 15: What is the R Function to divide a dataset into k clusters ?

Answer: Kmeans

Question 16: K Means algorithm assumes Eucledian Space/Distance

Answer: True

Question 17: What is the R function to apply hierarchical clustering to a matrix of distance objects ?

Answer: None

Question 18: ____________ of a set of points is defined using a distance measure .

Answer: Similarity

Question 19: A centroid is a valid point in a non-Eucledian space .

Answer: False

Question 20: What is the overall complexity of the the Agglomerative Hierarchical Clustering ?

Answer: O(N^3)

Question 21: _____________ is when points don't move between clusters and centroids stabilize.

Answer: Convergence

Question 22: ___________ is a way of finding the k value for k means clustering.

Answer: Cross Validation

Question 23: Sampling is one technique to pick the initial k points in K Means Clustering

Answer: True

Question 24: K Means algorithm assumes Eucledian Space/Distance

Answer: True

Question 25: What is the R function to apply hierarchical clustering to a matrix of distance objects ?

Answer: hclust()