- 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 QUESTIONS
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
What is true about Residuals?