- Supervised Learning
- Classification
- Regression
- Time Series Forecasting
- Unsupervised Learning
- Clustering
- K-Means Clustering
- Hierarchical Clustering
- Semi-Supervised Learning
- Reinforcement Learning(ML)
- Deep Learning(ML)
- Transfer Learning(ML)
- Ensemble Learning
- Explainable AI (XAI)
- Bayesian Learning
- Decision Trees
- Support Vector Machines (SVMs)
- Instance-Based Learning
- Rule-Based Learning
- Neural Networks
- Evolutionary Algorithms
- Meta-Learning
- Multi-Task Learning
- Metric Learning
- Few-Shot Learning
- Adversarial Learning
- Data Pre Processing
- Natural Language Processing(ML)

# Regression QUIZ - MCQ QUESTIONS AND ANSWERS

Question: 1

## Suppose you have to predict the salary of an employee from their years of experience where the dataset has a salary range from 10000 to 50000. In which of the intervals your regressive model should predict?

Question: 2

## In simple linear regression, if you change the input value by 1 then output value will be changed by:

Question: 3

## You can compute the residual by-

Question: 4

## How to see the value of residuals geometrically

Question: 5

## The equation of the regression line is y = 5x + 3. Predict y when x = 8.

Question: 6

## The equation of the regression line is y = 8x - 2. Compute the residual for the point (4, 28)

Question: 7

## What would be the best regression model for more than one independent variable?

Question: 8

## Suppose you have observed that you data has an exponential growth tendency. Then what regression model you should use-

Question: 9

## Can we perform linear regression with a neural network?

Question: 10

## If you get a poor accuracy using a simple linear regression model. What will be the cause behind it-

Question: 11

## If your data grows in a non-linear fashion. Which model won’t perform well?

Question: 12

## Suppose you got a training accuracy of 90% and a test accuracy of 50%. What happened with your model-

Question: 13

## What is a support vector?

Question: 14

## What is a kernel?

Question: 15

## Which of the following is not a kernel?

Question: 16

## What does epsilon represent in Support Vector Regression?

Question: 17

## In Regression, a decision tree splits the dataset based on-

Question: 18

## Which one is a different algorithm?

Question: 19

## Which one is not a better algorithm in the sense of overfitting?

Question: 20

## If the actual value of a data point is 50 and the predicted value is 55, what will be the Mean Absolute Error(MAE)

Question: 21

## Which of the following is a regression algorithm?

Question: 22

## Suppose you have to predict the salary of employees from their experience. This is a-

Question: 23

## Regression is a-

Question: 24

## Which of the following is/are true about Normal Equation?

Question: 25

## Which methods are used to find the best fit line in linear regression?

Question: 26

## What will happen when you increase the size of training data?

Question: 27

## If you fit 2 degree polynomial in linear regression-

Question: 28

## Which of the following evaluation metrics can be used for Regression?

Question: 29

## Linear regression is-

Question: 30