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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