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8.1. Toy datasets — scikit-learn 1.7.2 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 -
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 -
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 -
Tweedie regression on insurance claims — ...
This example illustrates the use of Poisson, Gamma and Tweedie regression on the French Motor Third-Party Liability Claims dataset, and is inspired by an R tutorial 1. In this dataset, each sample ...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
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 -
Robust linear estimator fitting — scikit-...
Here a sine function is fit with a polynomial of order 3, for values close to zero. Robust fitting is demonstrated in different situations: No measurement errors, only modelling errors (fitting a s...scikit-learn.org/stable/auto_examples/linear_model/plot_robust_fit.html -
Agglomerative clustering with and without struc...
This example shows the effect of imposing a connectivity graph to capture local structure in the data. The graph is simply the graph of 20 nearest neighbors. There are two advantages of imposing a ...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.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 -
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 0.098 seconds) Launch binder Launch JupyterLite Download Jupyter noteb...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_loss_functions.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