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Question at position 10 Select all correct answers: Which of the following are common methods of feature selection? kNNPrincipal Component Analysis (PCA)Ridge RegressionMin Max ScalingBackward EliminationLasso RegressionForward Selection

Options
A.kNN
B.Principal Component Analysis (PCA)
C.Ridge Regression
D.Min Max Scaling
E.Backward Elimination
F.Lasso Regression
G.Forward Selection
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Question restatement: The prompt asks to select all correct answers for common methods of feature selection, listing several candidate methods and several incorrect ones. Option 1: kNN. This is a lazy learning algorithm used for classification or regression based on nearest neighbors. It is not a feature selection method, so it does not serve to select a subset of features for a model. It’s more about making predictions using distances rather than reducing features. Option 2: Principal Component Analysis (PCA). PCA is a dimensionality reduction technique that transforms the data into a new set of orthogonal components. While it reduces dimensionality, it does so by projecting onto components rather than s......Login to view full explanation

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