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1.Supervisedlearning¶·1.1.1.OrdinaryLeastSquares·1.1.2.Ridgeregressionandclassification·1.1.3.Lasso·1.1.4.Multi-taskLasso·1.1.5.Elastic-Net ...,1.Supervisedlearning¶·1.OrdinaryLeastSquares·1.1.·2.Ridgeregression ...
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1. Supervised learning | sklearn stable
1. Supervised learning¶ · 1.1.1. Ordinary Least Squares · 1.1.2. Ridge regression and classification · 1.1.3. Lasso · 1.1.4. Multi-task Lasso · 1.1.5. Elastic-Net ... Read More
1. Supervised learning — scikit | sklearn stable
1. Supervised learning¶ · 1. Ordinary Least Squares · 1.1. · 2. Ridge regression ... Read More
1.11. Ensemble methods — scikit | sklearn stable
By contrast, in boosting methods, base estimators are built sequentially and one ... Read More
6.3. Preprocessing data | sklearn stable
The sklearn.preprocessing package provides several common utility functions and transformer classes to change raw feature vectors into a representation that ... Read More
6.3. Preprocessing data — scikit | sklearn stable
In general, learning algorithms benefit from standardization of the data set. If ... Read More
8. Computing with scikit | sklearn stable
scikit-learn: machine learning in Python. ... 8. Computing with scikit-learn¶ ... Read More
An introduction to machine learning with scikit | sklearn stable
In scikit-learn, an estimator for classification is a Python object that ... Read More
An introduction to machine learning with scikit | sklearn stable
scikit-learn: machine learning in Python. ... A common practice in machine learning is to evaluate an algorithm by ... Read More
API Reference — scikit | sklearn stable
For reference on concepts repeated across the API, see Glossary of Common ... Read More
API Reference — scikit | sklearn stable
The sklearn.decomposition module includes matrix decomposition algorithms, ... Read More
Examples — scikit | sklearn stable
Examples illustrating the calibration of predicted probabilities of classifiers. Read More
Examples — scikit | sklearn stable
Examples concerning the sklearn.datasets module. Plot randomly generated ... Read More
Frequently Asked Questions — scikit | sklearn stable
Frequently Asked Questions¶. Here we try to give some answers to questions ... Read More
Getting Started — scikit | sklearn stable
Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, ... Read More
Installing scikit | sklearn stable
Install the latest official release. This is the best approach for most users. Read More
Installing scikit | sklearn stable
scikit-learn: machine learning in Python. Read More
scikit | sklearn stable
scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. Read More
scikit | sklearn stable
2023年12月6日 — The idea behind stability selection is to inject more noise into the original problem by generating bootstrap samples of the data, and to use a ... Read More
scikit | sklearn stable
scikit-learn Tutorials¶ · Statistical learning: the setting and the estimator ... Read More
scikit | sklearn stable
scikit-learn: machine learning in Python. ... External Tutorials · Videos. Note. Read More
scikit-learn | sklearn stable
scikit-learn: machine learning in Python. ... December 2019. scikit-learn 0.22 is available for download (Changelog). Scikit-learn from 0.21 requires Python 3.5 or ... Read More
scikit-learn | sklearn stable
Simple and efficient tools for predictive data analysis · Accessible to everybody, and reusable in various contexts · Built on NumPy, SciPy, and matplotlib · Open ... Read More
scikit-learn | sklearn stable
Simple and efficient tools for predictive data analysis · Accessible to everybody, and reusable in various contexts · Built on NumPy, SciPy, and matplotlib · Open ... Read More
sklearn.metrics | sklearn stable
The sklearn.metrics module includes score functions, performance metrics and ... Read More
sklearn.preprocessing.StandardScaler | sklearn stable
Centering and scaling happen independently on each feature by computing the relevant statistics on the samples in the training set. Mean and standard deviation ... Read More
User guide | sklearn stable
User Guide: Supervised learning- Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, ... Read More
User guide: contents | sklearn stable
User Guide¶. 1. Supervised learning · 1.1. Linear Models. Read More
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