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2.8. Density Estimation — scikit-learn 1....
Density estimation walks the line between unsupervised learning, feature engineering, and data modeling. Some of the most popular and useful density estimation techniques are mixture models such as...scikit-learn.org/stable/modules/density.html -
1.10. Decision Trees — scikit-learn 1.8.0...
Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning s...scikit-learn.org/stable/modules/tree.html -
9. Computing with scikit-learn — scikit-l...
Strategies to scale computationally: bigger data- Scaling with instances using out-of-core learning., Computational Performance- Prediction Latency, Prediction Throughput, Tips and Tricks., Paralle...scikit-learn.org/stable/computing.html -
1.13. Feature selection — scikit-learn 1....
The classes in the sklearn.feature_selection module can be used for feature selection/dimensionality reduction on sample sets, either to improve estimators’ accuracy scores or to boost their perfor...scikit-learn.org/stable/modules/feature_selection.html -
8.1. Toy datasets — scikit-learn 1.8.0 do...
scikit-learn comes with a few small standard datasets that do not require to download any file from some external website. They can be loaded using the following functions: These datasets are usefu...scikit-learn.org/stable/datasets/toy_dataset.html -
1.16. Probability calibration — scikit-le...
When performing classification you often want not only to predict the class label, but also obtain a probability of the respective label. This probability gives you some kind of confidence on the p...scikit-learn.org/stable/modules/calibration.html -
8. Dataset loading utilities — scikit-lea...
The sklearn.datasets package embeds some small toy datasets and provides helpers to fetch larger datasets commonly used by the machine learning community to benchmark algorithms on data that comes ...scikit-learn.org/stable/datasets.html -
Demo of OPTICS clustering algorithm — sci...
Finds core samples of high density and expands clusters from them. This example uses data that is generated so that the clusters have different densities. The OPTICS is first used with its Xi clust...scikit-learn.org/stable/auto_examples/cluster/plot_optics.html -
Plotting Cross-Validated Predictions — sc...
This example shows how to use cross_val_predict together with PredictionErrorDisplay to visualize prediction errors. We will load the diabetes dataset and create an instance of a linear regression ...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html -
SGD: convex loss functions — scikit-learn...
A plot that compares the various convex loss functions supported by SGDClassifier. Total running time of the script:(0 minutes 0.086 seconds) Launch binder Launch JupyterLite Download Jupyter noteb...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_loss_functions.html