This is a practice test on K-Means Clustering algorithm which is one of the most widely used clustering algorithm used to solve problems related with unsupervised learning. This can prove to be helpful and useful for machine learning interns / freshers / beginners planning to appear in upcoming machine learning interviews.
This practice tests consists of interview questions and answers in relation with following:
- Introduction to K-Means Clustering
- Cost function
Practice Test on K-Means Clustering
K-Means is which type of learning algorithm?
K-Means can be used to solve _____________ problems.
Which of the following algorithm has similarity with K-Means?
K-means algorithm can be used for which of the following?
K-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest _________
The goal for K-Means cost function is to ________ squared error function where error function represents distance between data points and cluster centroid
In K-Means, K stands for __________
Which of the following forms key step of K-Means clustering algorithm?
K-Means squared error function is related with which of the following?
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