Comparing, validating and choosing parameters and models. Applications: Improved accuracy via parameter tuning. Algorithms: Grid search, cross validation, metrics, and more... Feature extraction and normalization. Applications: Transforming input data such as text for use with machine learning algorithms.

2010年1月1日 · Polynomial regression: extending linear models with basis functions.

2011年9月21日 · scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the About us page for a list of core contributors.

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 evaluation, and many other utilities.

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed.

2025年2月1日 · What is Scikit-learn? Scikit-learn is an open-source, free Python library. It facilitates activities such as classifying data, clustering similar data, forecasting values, and simplifying data for tasks like dimensionality reduction.Additionally, it gives you the skills to prepare data, select the optimal model, and assess performance.

scikit-learn 1.6.1 API documentation with instant search, offline support, keyboard shortcuts, mobile version, and more.

scikit-learn is a Python module integrating classic machine learning algorithms in the tightly-knit world of scientific Python packages (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems that are accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for ...

The documentation of scikit-learn is very complete and didactic. Introduction to Machine Learning with Python, by Sarah Guido, Andreas Müller (notebooks available here).

One of the best known is Scikit-Learn, a package that provides efficient versions of a large number of common algorithms. Scikit-Learn is characterized by a clean, uniform, and streamlined API,...