## 31. Computers are best at learning

## 32. what is Feature scaling done before applying K-Mean algorithm?

## 33. Which of the following is true about Naive Bayes?

## 34. KDD represents extraction of

## 35. Linear Regression is a . . . . . . . . machine learning algorithm.

## 36. The probability that a person owns a sports car given that they subscribe to automotive magazine is 40%. We also know that 3% of the adult population subscribes to automotive magazine. The probability of a person owning a sports car given that they don't subscribe to automotive magazine is 30%. Use this information to compute the probability that a person subscribes to automotive magazine given that they own a sports car

## 37. Which among the following statements best describes our approach to learning decision trees

## 38. Which of the following techniques would perform better for reducing dimensions of a data set?

## 39. . . . . . . . . can be adopted when it's necessary to categorize a large amount of data with a few complete examples or when there's the need to impose some constraints to a clustering algorithm.

## 40. Binarize parameter in BernoulliNB scikit sets threshold for binarizing of sample features.

## Read More Section(Machine Learning)

Each Section contains maximum **100 MCQs question** on **Machine Learning**. To get more questions visit other sections.