Data Science, Machine Learning, Artificial Intelligence, Technology, Data Mining.
n_features): top_features = {} for i in range(pca_loadings.shape[0]): # Get the index of the n largest absolute values in the i-th principal component top_indices = np.argsort(np.abs(pca_loadings[i]))[-n_features:] # Create a dictionary of the top features and their loadings for the i-th principal