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Regression

Q. What is Elastic-net? Why is it better in comparison to Ridge and Lasso?
Q. How would you perform feature selection using Lasso?
Q. When to use Ridge Regression vs Lasso?
Q. What does L2 regularization (Ridge) mean?
Q. What does L1 regularization (Lasso) mean?
Q. What is Regularization?
Q. What is Tweedie Regression?
Q. What is Beta regression?
Q. What is Gamma Regression?
Q. Briefly discuss other models that fall within the scope of GLM.
Q. What about cases where a significant number of observations have a count of 0 (in the context of Poisson Regression)?
Q. What is overdispersion in Poisson Regression, and what are alternate specifications for when it is present?
Q. What is the cost function used in Poisson Regression?
Q. How does GLM adjust to the case of count data?
Q. What is a Generalized Linear Model (GLM)?
Q. What is non-negative least squares, and when is it used?
Q. What are potential problems encountered in Linear Regression?
Q. What is a high influence point?
Q. What is a high leverage point?
Q. What is an outlier?
Q. What is the difference between outliers, high leverage points, and high influence points?
Q. What is the difference between Regression and ANOVA?
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 some approaches for modeling non linear relationships?
Q. Differentiate between Linear Models and Non Linear Models
Q. What are the most common transformations when the target variable is not normally distributed?
Q. How can categorical predictors be incorporated 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 of the problems with stepwise selection approaches?
Q. What is Information Criteria (AIC, BIC)?
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. What are the evaluation criteria for a Linear Regression model?
Q. What is multicollinearity and how can that be identified?
Q. How is variability measured in Linear Regression?
Q. How are coefficients of linear regression estimated?
Q. What are some methods of Variable Selection?
Q. What are the assumptions of linear regression?
Q. Explain the concept of Linear Regression

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Explore Questions by Topics

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Deep Learning (52)
- DL Architectures (17)
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  - Sequence models (6)
  - Transformers (9)
- DL Basics (16)
- DL Training and Optimization (17)
Generative AI (2)
Machine Learning Basics (18)
Natural Language Processing (27)
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Statistics (34)
Supervised Learning (115)
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  - Logistic Regression (10)
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  - Support Vector Machine (9)
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  - Linear Regression (26)
  - Regularization (6)
Unsupervised Learning (55)
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  - Clustering Evaluations (6)
  - Distance Measures (9)
  - Gaussian Mixture Models (5)
  - Hierarchical Clustering (3)
  - K-Means Clustering (9)
- Dimensionality Reduction (9)

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Other Questions in Regression

What is Within Cluster Sum of Squares (WCSS)?
What are some approaches for modeling non linear relationships?
What is Kernel PCA?
What problems would arise from using a regular linear regression to model a binary outcome?
What is the problem with using a generic list of stop words?
What is Classification?

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