**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 ?

- Divisive
- None of the Options
- Point Assignment
- Agglomerative

Answer: 4)Agglomerative

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

- Eucledian
- Manhattan
- Jaccard
- Cosine

Answer: 3)Jaccard

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

- True
- False

Answer: 1)True

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

- Active
- Passive
- Unsupervised
- Supervised

Answer: 3)Unsupervised

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

- Similarity
- Adjacency
- Dissimilarity
- 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 ?

- O(N^2)
- O(N)
- O(N^4)
- O(N^3)

Answer: 4)O(N^3)

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

- False
- True

Answer: 1)False

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

- None of the Options
- Closure Point
- Clusteroid
- Affinity Point

Answer: 3)Clusteroid

4.___________ measures the goodness of a cluster

- Cohesion
- Clusteroid
- Centroid
- None of the options

Answer: 1)Cohesion

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

- Dendogram
- None of the Options
- Graph
- Scatter Plot

Answer: 1)Dendogram

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

- False
- True

Answer: 1)False

**Quiz on K Means Clustering**

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

- True
- False

Answer: 1)True

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

- True
- False

Answer: 1)True

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

- True
- False

Answer: 2)False

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

- Centroid Measure
- None of the Options
- Random Walk
- Cross Validation

Answer: 4)Cross Validation

5.K Means algorithm assumes Eucledian Space/Distance

- True
- False

Answer: 1)True

**Clustering Final Assessment**

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

- None of the options
- Stationary
- Convergence

Answer: 3)Convergence

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

- Active
- Passive
- Supervised
- Unsupervised

Answer: 4)Unsupervised

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

- True
- False

Answer: 2)False

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

- kmeans()
- clusters()
- kclusters()
- None of the Options

Answer: 1)kmeans()

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

- False
- True

Answer: 1)False

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

- hclust()
- None of the Options
- hierarchical()
- cluster()

Answer: 1)hclust()

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