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Linear Regression

Q. Explain the concept of Linear Regression
Q. How are coefficients of linear regression estimated?
Q. What are the assumptions of linear regression?
Q. How is variability measured in Linear Regression?
Q. What are the evaluation criteria for a Linear Regression model?
Q. How can categorical predictors be incorporated in linear regression?
Q. What are potential problems encountered in Linear Regression?
Q. Suppose there are a large number of predictors ‘p’. What is the best approach to find out if any of the p predictors are helpful in predicting the response ‘y’?
Q. What are some approaches for modeling non linear relationships?
Q. What are the most common transformations when the target variable is not normally distributed?
Q. What is multicollinearity and how can that be identified?
Q. Why does multicollinearity result in poor estimates of coefficients in linear regression?
Q. Doesn’t polynomial regression violate the multicollinearity assumption for Linear Regression?
Q. What are the various measures of error (MSE, RMSE, MAE)?
Q. What is R-squared and adjusted R-squared?
Q. What is Global F-Test?
Q. Differentiate between Linear Models and Non Linear Models
Q. What is Information Criteria (AIC, BIC)?
Q. What are some methods of Variable Selection?
Q. What are some of the problems with stepwise selection approaches?
Q. What is the difference between Regression and ANOVA?
Q. What is an outlier?
Q. What is a high leverage point?
Q. What is a high influence point?
Q. What is the difference between outliers, high leverage points, and high influence points?
Q. What is non-negative least squares, and when is it used?

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Computer Vision (1)
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Machine Learning Basics (18)
Deep Learning (52)
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- DL Architectures (17)
  - Feedforward Network / MLP (2)
  - Sequence models (6)
  - Transformers (9)
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Supervised Learning (115)
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  - Linear Regression (26)
  - Generalized Linear Models (9)
  - Regularization (6)
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  - Logistic Regression (10)
  - Support Vector Machine (9)
  - Ensemble Learning (24)
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  - Classification Evaluations (9)
Unsupervised Learning (55)
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  - Distance Measures (9)
  - K-Means Clustering (9)
  - Hierarchical Clustering (3)
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  - Clustering Evaluations (6)
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Other Questions in Linear Regression

What are options to calibrate probabilities produced from the output of a classifier that does not produce natural probabilities?
What are the subtypes of Cross Validation?
What is Specificity?
Explain the concept and working of the Random Forest model
How does a learning curve give insight into whether the model is under- or over-fitting?
What is the difference between Discriminative and Generative models?

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