Machine Learning II: Linear Model Selection to Unsupervised Learning

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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?

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?

K-means clustering (correct)

Cross-validation

Feature selection

Principle Components Analysis (PCA)

What does the Lasso method primarily focus on in machine learning?

Selecting a subset of predictors Signup and view all the answers

Which technique is used for dimension reduction in machine learning?

Principle Components Analysis (PCA) Signup and view all the answers

What is the main benefit of using Ridge Regression over ordinary linear regression?

Reduction of variance and overfitting Signup and view all the answers

In machine learning, which method is primarily used for selecting a subset of predictors?

Best subset selection Signup and view all the answers

What is the main difference between Ridge Regression and Lasso in the context of machine learning?

Ridge Regression shrinks all coefficients equally, whereas Lasso can shrink some coefficients to zero. Signup and view all the answers

Which method in machine learning involves shrinking the estimated coefficients towards zero to reduce model variance?

Lasso Signup and view all the answers

What is the primary goal of feature selection techniques in machine learning?

To identify the most important predictors for the model Signup and view all the answers

Among the options, which technique is commonly used for unsupervised learning in machine learning?

Hierarchical clustering Signup and view all the answers

Which method is employed in machine learning to reduce the number of dimensions in a dataset?

Principle Components Analysis (PCA) Signup and view all the answers

'Shrinkage' in machine learning models typically refers to what action?

Reducing the magnitude of coefficients towards zero Signup and view all the answers

Machine Learning II: Linear Model Selection to Unsupervised Learning

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Questions and Answers

Which method is used for shrinking the estimated coefficients towards zero to reduce variance?

In machine learning, what is the purpose of subset selection?

Which technique is NOT associated with linear model selection and regularization?

What does the Lasso method primarily focus on 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?

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?

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?

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?

'Shrinkage' in machine learning models typically refers to what action?

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