Clustering the ensemble | Fresco Play

Clustering the ensemble | Fresco Play

Monday, May 22, 2023
~ 2 min read
Clustering the ensemble | Fresco Play

Question 1: nan

Answer: nan


Question 2: Members of the same cluster are far away / distant from each other .

Answer: False


Question 3: unsupervised learning focuses on understanding the data and its underlying pattern.

Answer: True


Question 4: 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 5: What is a preferred distance measure while dealing with sets ?

Answer: jaccard


Question 6: Which learning is the method of finding structure in the data without labels.

Answer: unsupervised


Question 7: __________ measures the goodness of a cluster

Answer: cohesion


Question 8: A centroid is a valid point in a non-Eucledian space .

Answer: False


Question 9: ___________ of two points is the average of the two points in Eucledian Space.

Answer: centroid


Question 10: The ______ is a visual representation of how the data points are merged to form clusters.

Answer: dendogram


Question 11: What is the overall complexity of the the Agglomerative Hierarchical Clustering ?

Answer: o n 3


Question 12: ___________ is the data point that is closest to the other point in the cluster.

Answer: clusteroid


Question 13: Sampling is one technique to pick the initial k points in K Means Clustering

Answer: True


Question 14: The number of rounds for convergence in k means clustering can be lage

Answer: True


Question 15: Hierarchical Clustering is a suggested approach for Large Data Sets

Answer: False


Question 16: __________ is a way of finding the k value for k means clustering.

Answer: cross


Question 17: What is the R Function to divide a dataset into k clusters ?

Answer: kmeans


Question 18: _____________ is when points don't move between clusters and centroids stabilize.

Answer: Stationary


Question 19: K Means algorithm assumes Eucledian Space/Distance

Answer: True


Question 20: What is the R function to apply hierarchical clustering to a matrix of distance objects ?

Answer: None


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