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inplace_swap_row — scikit-learn 1.7.1 documenta...
Skip to main content Back to top Ctrl + K GitHub Choose version inplace_swap_row # sklearn.utils.sparsefuncs. inplace...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_swap_row.html -
add_dummy_feature — scikit-learn 1.7.1 document...
Skip to main content Back to top Ctrl + K GitHub Choose version add_dummy_feature # sklearn.preprocessing. add_dummy_...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.add_dummy_feature.html -
check_random_state — scikit-learn 1.7.1 documen...
Gallery examples: Empirical evaluation of the impact of k-means initialization MNIST classification using multinomial logistic + L1 Manifold Learning methods on a severed sphere Isotonic Regression...scikit-learn.org/stable/modules/generated/sklearn.utils.check_random_state.html -
check_X_y — scikit-learn 1.7.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version check_X_y # sklearn.utils. check_X_y ( X , y , accept...scikit-learn.org/stable/modules/generated/sklearn.utils.check_X_y.html -
Features in Histogram Gradient Boosting Trees —...
Histogram-Based Gradient Boosting(HGBT) models may be one of the most useful supervised learning models in scikit-learn. They are based on a modern gradient boosting implementation comparable to Li...scikit-learn.org/stable/auto_examples/ensemble/plot_hgbt_regression.html -
Early stopping of Stochastic Gradient Descent —...
Stochastic Gradient Descent is an optimization technique which minimizes a loss function in a stochastic fashion, performing a gradient descent step sample by sample. In particular, it is a very ef...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_early_stopping.html -
Outlier detection on a real data set — scikit-l...
This example illustrates the need for robust covariance estimation on a real data set. It is useful both for outlier detection and for a better understanding of the data structure. We selected two ...scikit-learn.org/stable/auto_examples/applications/plot_outlier_detection_wine.html -
Image denoising using kernel PCA — scikit-learn...
This example shows how to use KernelPCA to denoise images. In short, we take advantage of the approximation function learned during fit to reconstruct the original image. We will compare the result...scikit-learn.org/stable/auto_examples/applications/plot_digits_denoising.html -
Blind source separation using FastICA — scikit-...
An example of estimating sources from noisy data. Independent component analysis (ICA) is used to estimate sources given noisy measurements. Imagine 3 instruments playing simultaneously and 3 micro...scikit-learn.org/stable/auto_examples/decomposition/plot_ica_blind_source_separation.html -
Recognizing hand-written digits — scikit-learn ...
This example shows how scikit-learn can be used to recognize images of hand-written digits, from 0-9. Digits dataset: The digits dataset consists of 8x8 pixel images of digits. The images attribute...scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html