AI, Dimensionality Reduction, Machine Learning, Python, Data Science.
test_size=0.2, random_state=42) # Standardize the features (important for SVD) scaler = StandardScaler() X_train = scaler.fit_transform(X_train) X_test = scaler.transform(X_test) # Initialize SVD and fit on the training data svd = TruncatedSVD(n_components=X_train.shape[1] - 1) # Use one less