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 …
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 …
2.3. Clustering — scikit-learn 1.8.0 documentation
The current implementation uses ball trees and kd-trees to determine the neighborhood of points, which avoids calculating the full distance matrix (as was done in scikit-learn versions before 0.14). The …
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 …
2.7. Novelty and Outlier Detection - scikit-learn
The scikit-learn project provides a set of machine learning tools that can be used both for novelty or outlier detection. This strategy is implemented with objects learning in an unsupervised way from the …
RandomForestRegressor — scikit-learn 1.8.0 documentation
Plot individual and voting regression predictions Imputing missing values with variants of IterativeImputer Imputing missing values before building an estimator Release Highlights for scikit-learn 0.24 Release …
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 …