Installing scikit-learn — scikit-learn 1.6.1 documentation
There are different ways to install scikit-learn: Install the latest official release. This is the best approach for most users. It will provide a stable version and pre-built packages are availabl...
scikit-learn: machine learning in Python — scikit-learn 1.6.1 …
"scikit-learn's ease-of-use, performance and overall variety of algorithms implemented has proved invaluable [...]" "The great benefit of scikit-learn is its fast learning curve [...]" "It allows us to do …
Getting Started — scikit-learn 1.6.1 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, …
PCA — scikit-learn 1.6.1 documentation
Release Highlights for scikit-learn 1.4 A demo of K-Means clustering on the handwritten digits data Principal Component Regression vs Partial Least Squares Regression
1. Supervised learning — scikit-learn 1.6.1 documentation
Jan 1, 2010 · 8. Computing with scikit-learn. 8.1. Strategies to scale computationally: bigger data; 8.2. Computational Performance; 8.3. Parallelism, resource management, and configuration; …
NMF — scikit-learn 1.6.1 documentation
Learn a NMF model for the data X and returns the transformed data. This is more efficient than calling fit followed by transform. Parameters: X {array-like, sparse matrix} of shape …
1.9. Naive Bayes — scikit-learn 1.6.1 documentation
For an overview of available strategies in scikit-learn, see also the out-of-core learning documentation. Note The partial_fit method call of naive Bayes models introduces some …
scikit-learn: machine learning in Python — scikit-learn 1.0.2 …
May 2020. scikit-learn 0.23.0 is available for download . Scikit-learn from 0.23 requires Python 3.6 or newer. March 2020. scikit-learn 0.22.2 is available for download ( Changelog ).
1.10. Decision Trees — scikit-learn 1.6.1 documentation
For instance, in the example below, decision trees learn from data to approximate a sine curve with a set of if-then-else decision rules. The deeper the tree, the more complex the decision …
2.3. Clustering — scikit-learn 1.6.1 documentation
Clustering of unlabeled data can be performed with the module sklearn.cluster. Each clustering algorithm comes in two variants: a class, that implements the fit method to learn the clusters …