Clustering – The Data Ensemble MCQ with Answer

Hello Friends in this post we are going to discuss about Clustering – The Data Ensemble MCQ with Answer | clustering – the data ensemble fresco play answers | Clustering – The Data Ensemble TCS Answer Dump | Clustering – The Data Ensemble TFactor Answer | Clustering – The Data Ensemble Objective type question

Q1.hat is a preferred distance measure while dealing with sets ?
Jaccard — Correct

Q2.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

Q3.Which learning is the method of finding structure in the data without labels.
Unsupervised — Correct

Q4.______ of a set of points is defined using a distance measure .
Similarity — Correct

Q5.Members of the same cluster are far away / distant from each other .
False — Correct

Q6.Unsupervised learning focuses on understanding the data and its underlying pattern.
True — Correct

Q7._______ of two points is the average of the two points in Eucledian Space.
Centroid — Correct

Q8.A centroid is a valid point in a non-Eucledian space .
False — Correct

Q9.What is the overall complexity of the the Agglomerative Hierarchical Clustering ?
O(N^3) — Correct

Q10._____ measures the goodness of a cluster
Cohesion — Correct

Q11.______ is the data point that is closest to the other point in the cluster.
Clusteroid — Correct

Q12. The _______ is a visual representation of how the data points are merged to form clusters.
Dendogram — Correct

Q13.____ is when points don’t move between clusters and centroids stabilize.
Convergence — Correct

Q14.______ is a way of finding the k value for k means clustering.
Cross Validation — Correct

Q15.The number of rounds for convergence in k means clustering can be lage
True — Correct

Q16.Sampling is one technique to pick the initial k points in K Means Clustering
True — Correct

Q17.K Means algorithm assumes Eucledian Space/Distance
True — Correct

Q18.What is the R Function to divide a dataset into k clusters ?
kclusters() — Wrong

Q19.What is the R function to apply hierarchical clustering to a matrix of distance objects ?
hclust() — Correct

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