## 1. Suppose you are training a linear regression model. Now consider these points.

1. Overfitting is more likely if we have less data

2. Overfitting is more likely when the hypothesis space is small.Which of the above statement(s) are correct?

1. Overfitting is more likely if we have less data

2. Overfitting is more likely when the hypothesis space is small.Which of the above statement(s) are correct?

## 2. Gini index does not favour equal sized partitions.

## 3. what is the function of 'Unsupervised Learning'?

## 4. In an election, N candidates are competing against each other and people are voting for either of the candidates. Voters don't communicate with each other while casting their votes. Which of the following ensemble method works similar to above-discussed election procedure? Hint: Persons are like base models of ensemble method.

## 5. The soft margin SVM is more preferred than the hard-margin SVM when-

## 6. Which of the following option is true regarding "Regression" and "Correlation"?

Note: y is dependent variable and x is independent variable.

Note: y is dependent variable and x is independent variable.

## 7. A nearest neighbor approach is best used

## 8. For the given weather data, what is the probability that players will play if weather is sunny

## 9. Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

## 10. Which one of the following is the main reason for pruning a Decision Tree?

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