numpy sklearn.decomposition.PCA This function first applies PCA (Principal Component Analysis) to reduce the dimensions of the dataset, and then uses PermutationImportance to explain the importance of the principal components. PermutationImportance evaluates the importance of features by randomly shuffling feature values and observing the change in model performance. The type of code 2024-12-16 12:16:44 15 views
