Clustering - The Data Ensemble Fresco Play MCQs Answers

Clustering - The Data Ensemble Fresco Play MCQs Answers

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Course Path: Data Science/MACHINE LEARNING METHODS/Clustering - The Data Ensemble

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Quiz on Clustering Overview

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

1. Divisive
2. None of the Options
3. Point Assignment
4. Agglomerative

Answer: 4)Agglomerative

2.What is a preferred distance measure while dealing with sets ?

1. Eucledian
2. Manhattan
3. Jaccard
4. Cosine

Answer: 3)Jaccard

3.Unsupervised learning focuses on understanding the data and its underlying pattern.

1. True
2. False

Answer: 1)True

4.Which learning is the method of finding structure in the data without labels.

1. Active
2. Passive
3. Unsupervised
4. Supervised

Answer: 3)Unsupervised

5.____________ of a set of points is defined using a distance measure .

1. Similarity
2. Adjacency
3. Dissimilarity
4. None of the options

Answer: 1)Similarity

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Quiz on Hierarchical Clustering

1.What is the overall complexity of the the Agglomerative Hierarchical Clustering ?

1. O(N^2)
2. O(N)
3. O(N^4)
4. O(N^3)

Answer: 4)O(N^3)

2.A centroid is a valid point in a non-Eucledian space .

1. False
2. True

Answer: 1)False

3.___________ is the data point that is closest to the other point in the cluster.

1. None of the Options
2. Closure Point
3. Clusteroid
4. Affinity Point

Answer: 3)Clusteroid

4.___________ measures the goodness of a cluster

1. Cohesion
2. Clusteroid
3. Centroid
4. None of the options

Answer: 1)Cohesion

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

1. Dendogram
2. None of the Options
3. Graph
4. Scatter Plot

Answer: 1)Dendogram

6.A centroid is a valid point in a non-Eucledian space .

1. False
2. True

Answer: 1)False

Quiz on K Means Clustering

1.The number of rounds for convergence in k means clustering can be lage

1. True
2. False

Answer: 1)True

2.Sampling is one technique to pick the initial k points in K Means Clustering

1. True
2. False

Answer: 1)True

3.Hierarchical Clustering is a suggested approach for Large Data Sets

1. True
2. False

Answer: 2)False

4.___________ is a way of finding the k value for k means clustering.

1. Centroid Measure
2. None of the Options
3. Random Walk
4. Cross Validation

Answer: 4)Cross Validation

5.K Means algorithm assumes Eucledian Space/Distance

1. True
2. False

Answer: 1)True

Clustering Final Assessment

1._____________ is when points don't move between clusters and centroids stabilize.

1. None of the options
2. Stationary
3. Convergence

Answer: 3)Convergence

2.Which learning is the method of finding structure in the data without labels.

1. Active
2. Passive
3. Supervised
4. Unsupervised

Answer: 4)Unsupervised

3.Members of the same cluster are far away / distant from each other .

1. True
2. False

Answer: 2)False

4.What is the R Function to divide a dataset into k clusters ?

1. kmeans()
2. clusters()
3. kclusters()
4. None of the Options

Answer: 1)kmeans()

5.A centroid is a valid point in a non-Eucledian space .

1. False
2. True

Answer: 1)False

6.What is the R function to apply hierarchical clustering to a matrix of distance objects ?

1. hclust()
2. None of the Options
3. hierarchical()
4. cluster()

Answer: 1)hclust()

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