Podcast
Questions and Answers
Which method is used for shrinking the estimated coefficients towards zero to reduce variance?
Which method is used for shrinking the estimated coefficients towards zero to reduce variance?
- Polynomial regression
- Linear regression
- Ridge Regression (correct)
- Best subset selection
In machine learning, what is the purpose of subset selection?
In machine learning, what is the purpose of subset selection?
- Removing outliers from the data
- Selecting the best predictors from a pool (correct)
- Reducing variance
- Increasing model complexity
Which technique is NOT associated with linear model selection and regularization?
Which technique is NOT associated with linear model selection and regularization?
- K-means clustering (correct)
- Cross-validation
- Feature selection
- Principle Components Analysis (PCA)
What does the Lasso method primarily focus on in machine learning?
What does the Lasso method primarily focus on in machine learning?
Which technique is used for dimension reduction in machine learning?
Which technique is used for dimension reduction in machine learning?
What is the main benefit of using Ridge Regression over ordinary linear regression?
What is the main benefit of using Ridge Regression over ordinary linear regression?
In machine learning, which method is primarily used for selecting a subset of predictors?
In machine learning, which method is primarily used for selecting a subset of predictors?
What is the main difference between Ridge Regression and Lasso in the context of machine learning?
What is the main difference between Ridge Regression and Lasso in the context of machine learning?
Which method in machine learning involves shrinking the estimated coefficients towards zero to reduce model variance?
Which method in machine learning involves shrinking the estimated coefficients towards zero to reduce model variance?
What is the primary goal of feature selection techniques in machine learning?
What is the primary goal of feature selection techniques in machine learning?
Among the options, which technique is commonly used for unsupervised learning in machine learning?
Among the options, which technique is commonly used for unsupervised learning in machine learning?
Which method is employed in machine learning to reduce the number of dimensions in a dataset?
Which method is employed in machine learning to reduce the number of dimensions in a dataset?
'Shrinkage' in machine learning models typically refers to what action?
'Shrinkage' in machine learning models typically refers to what action?
