scikit-learn: machine learning in Python — scikit-learn 1.8.0 …
scikit-learn Machine Learning in Python Getting Started Release Highlights for 1.8
Installing scikit-learn — scikit-learn 1.8.0 documentation
Install the version of scikit-learn provided by your operating system or Python distribution. This is a quick option for those who have operating systems or Python distributions that distribute scikit-learn.
Getting Started — scikit-learn 1.8.0 documentation
Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model …
API Reference — scikit-learn 1.8.0 documentation
This is the class and function reference of scikit-learn. Please refer to the full user guide for further details, as the raw specifications of classes and functions may not be enough to give full guidelines …
User Guide — scikit-learn 1.8.0 documentation
Jan 1, 2010 · 9. Computing with scikit-learn 9.1. Strategies to scale computationally: bigger data 9.1.1. Scaling with instances using out-of-core learning 9.2. Computational Performance 9.2.1. Prediction …
1. Supervised learning — scikit-learn 1.8.0 documentation
Jan 1, 2010 · Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, Multi-task Elastic-Net, Least Angle Regression, LARS Lasso, Orthogonal …
train_test_split — scikit-learn 1.8.0 documentation
Gallery examples: Image denoising using kernel PCA Faces recognition example using eigenfaces and SVMs Model Complexity Influence Prediction Latency Lagged features for time series forecasting …
sklearn — scikit-learn 1.8.0 documentation
Configure global settings and get information about the working environment.
Examples — scikit-learn 1.8.0 documentation
This is the gallery of examples that showcase how scikit-learn can be used. Some examples demonstrate the use of the API in general and some demonstrate specific applications in tutorial form.
LogisticRegression — scikit-learn 1.8.0 documentation
LogisticRegression # class sklearn.linear_model.LogisticRegression(penalty='deprecated', *, C=1.0, l1_ratio=0.0, dual=False, tol=0.0001, fit_intercept=True, intercept_scaling=1, class_weight=None, …