<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <title>User guide: contents — scikits.learn v0.6.0 documentation</title> <link rel="stylesheet" href="_static/nature.css" type="text/css" /> <link rel="stylesheet" href="_static/pygments.css" type="text/css" /> <script type="text/javascript"> var DOCUMENTATION_OPTIONS = { URL_ROOT: '', VERSION: '0.6.0', COLLAPSE_INDEX: false, FILE_SUFFIX: '.html', HAS_SOURCE: true }; </script> <script type="text/javascript" src="_static/jquery.js"></script> <script type="text/javascript" src="_static/underscore.js"></script> <script type="text/javascript" src="_static/doctools.js"></script> <link rel="shortcut icon" href="_static/favicon.ico"/> <link rel="author" title="About these documents" href="about.html" /> <link rel="top" title="scikits.learn v0.6.0 documentation" href="index.html" /> </head> <body> <div class="header-wrapper"> <div class="header"> <p class="logo"><a href="index.html"> <img src="_static/scikit-learn-logo-small.png" alt="Logo"/> </a> </p><div class="navbar"> <ul> <li><a href="install.html">Download</a></li> <li><a href="support.html">Support</a></li> <li><a href="#">User Guide</a></li> <li><a href="auto_examples/index.html">Examples</a></li> <li><a href="developers/index.html">Development</a></li> </ul> <div class="search_form"> <div id="cse" style="width: 100%;"></div> <script src="http://www.google.com/jsapi" type="text/javascript"></script> <script type="text/javascript"> google.load('search', '1', {language : 'en'}); google.setOnLoadCallback(function() { var customSearchControl = new google.search.CustomSearchControl('016639176250731907682:tjtqbvtvij0'); customSearchControl.setResultSetSize(google.search.Search.FILTERED_CSE_RESULTSET); var options = new google.search.DrawOptions(); options.setAutoComplete(true); customSearchControl.draw('cse', options); }, true); </script> </div> </div> <!-- end navbar --></div> </div> <div class="content-wrapper"> <!-- <div id="blue_tile"></div> --> <div class="sphinxsidebar"> <div class="rel"> <a href="genindex.html" title="General Index" accesskey="I">index</a> </div> <h3>Contents</h3> <ul> <li><a class="reference internal" href="#">User guide: contents</a><ul> </ul> </li> </ul> </div> <div class="content"> <div class="documentwrapper"> <div class="bodywrapper"> <div class="body"> <div class="section" id="user-guide-contents"> <h1>User guide: contents<a class="headerlink" href="#user-guide-contents" title="Permalink to this headline">ΒΆ</a></h1> <style type="text/css"> div.bodywrapper blockquote { margin: 0 ; } div.toctree-wrapper ul { margin: 0 ; padding-left: 0px ; } li.toctree-l1 { padding: 0 ; list-style-type: none; font-size: 150% ; font-family: Arial, sans-serif; background-color: #BED4EB; font-weight: normal; color: #212224; margin-left : 0; font-weight: bold; } li.toctree-l1 a { padding: 0 0 0 10px ; } li.toctree-l2 { padding: 0.25em 0 0.25em 0 ; list-style-type: none; background-color: #FFFFFF; font-size: 90% ; font-weight: bold; } li.toctree-l2 ul { padding-left: 40px ; } li.toctree-l3 { font-size: 70% ; list-style-type: none; font-weight: normal; } li.toctree-l4 { font-size: 85% ; list-style-type: none; font-weight: normal; } </style><p>This is the html version of user guide. A PDF version for printing can be found <a class="reference external" href="http://sourceforge.net/projects/scikit-learn/files/user_guide.pdf/download">here</a>.</p> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="install.html">1. Installing <cite>scikits.learn</cite></a><ul> <li class="toctree-l2"><a class="reference internal" href="install.html#installing-an-official-release">1.1. Installing an official release</a><ul> <li class="toctree-l3"><a class="reference internal" href="install.html#installing-from-source">1.1.1. Installing from source</a><ul> <li class="toctree-l4"><a class="reference internal" href="install.html#easy-install">1.1.1.1. Easy install</a></li> <li class="toctree-l4"><a class="reference internal" href="install.html#from-source-package">1.1.1.2. From source package</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="install.html#windows-installer">1.1.2. Windows installer</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="install.html#third-party-distributions-of-scikits-learn">1.2. Third party distributions of scikits.learn</a><ul> <li class="toctree-l3"><a class="reference internal" href="install.html#debian-and-derivatives-ubuntu">1.2.1. Debian and derivatives (Ubuntu)</a></li> <li class="toctree-l3"><a class="reference internal" href="install.html#enthought-python-distribution">1.2.2. Enthought python distribution</a></li> <li class="toctree-l3"><a class="reference internal" href="install.html#macports">1.2.3. Macports</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="install.html#bleeding-edge">1.3. Bleeding Edge</a></li> <li class="toctree-l2"><a class="reference internal" href="install.html#testing">1.4. Testing</a></li> </ul> </li> <li class="toctree-l1"><a class="reference internal" href="tutorial.html">2. Getting started: an introduction to machine learning with scikits.learn</a><ul> <li class="toctree-l2"><a class="reference internal" href="tutorial.html#machine-learning-the-problem-setting">2.1. Machine learning: the problem setting</a></li> <li class="toctree-l2"><a class="reference internal" href="tutorial.html#loading-an-example-dataset">2.2. Loading an example dataset</a></li> <li class="toctree-l2"><a class="reference internal" href="tutorial.html#learning-and-predicting">2.3. Learning and Predicting</a></li> </ul> </li> <li class="toctree-l1"><a class="reference internal" href="supervised_learning.html">3. Supervised learning</a><ul> <li class="toctree-l2"><a class="reference internal" href="modules/linear_model.html">3.1. Generalized Linear Models</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#ordinary-least-squares-ols">3.1.1. Ordinary Least Squares (OLS)</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/linear_model.html#ols-complexity">3.1.1.1. OLS Complexity</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#ridge-regression">3.1.2. Ridge Regression</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/linear_model.html#ridge-complexity">3.1.2.1. Ridge Complexity</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#lasso">3.1.3. Lasso</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#elastic-net">3.1.4. Elastic Net</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#least-angle-regression">3.1.5. Least Angle Regression</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#lars-lasso">3.1.6. LARS Lasso</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/linear_model.html#mathematical-formulation">3.1.6.1. Mathematical formulation</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#bayesian-regression">3.1.7. Bayesian Regression</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/linear_model.html#bayesian-ridge-regression">3.1.7.1. Bayesian Ridge Regression</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#automatic-relevance-determination-ard">3.1.8. Automatic Relevance Determination - ARD</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/linear_model.html#id3">3.1.8.1. Mathematical formulation</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/linear_model.html#stochastic-gradient-descent-sgd">3.1.9. Stochastic Gradient Descent - SGD</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/svm.html">3.2. Support Vector Machines</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#classification">3.2.1. Classification</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#regression">3.2.2. Regression</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#density-estimation-outliers-detection">3.2.3. Density estimation, outliers detection</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#support-vector-machines-for-sparse-data">3.2.4. Support Vector machines for sparse data</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#complexity">3.2.5. Complexity</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#tips-on-practical-use">3.2.6. Tips on Practical Use</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#kernel-functions">3.2.7. Kernel functions</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/svm.html#custom-kernels">3.2.7.1. Custom Kernels</a><ul> <li class="toctree-l5"><a class="reference internal" href="modules/svm.html#using-python-functions-as-kernels">3.2.7.1.1. Using python functions as kernels</a></li> <li class="toctree-l5"><a class="reference internal" href="modules/svm.html#using-the-gram-matrix">3.2.7.1.2. Using the Gram matrix</a></li> </ul> </li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#mathematical-formulation">3.2.8. Mathematical formulation</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/svm.html#svc">3.2.8.1. SVC</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/svm.html#nusvc">3.2.8.2. NuSVC</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#frequently-asked-questions">3.2.9. Frequently Asked Questions</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/svm.html#implementation-details">3.2.10. Implementation details</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/sgd.html">3.3. Stochastic Gradient Descent</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#classification">3.3.1. Classification</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#regression">3.3.2. Regression</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#stochastic-gradient-descent-for-sparse-data">3.3.3. Stochastic Gradient Descent for sparse data</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#complexity">3.3.4. Complexity</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#tips-on-practical-use">3.3.5. Tips on Practical Use</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#mathematical-formulation">3.3.6. Mathematical formulation</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/sgd.html#id1">3.3.6.1. SGD</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/sgd.html#implementation-details">3.3.7. Implementation details</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/neighbors.html">3.4. Nearest Neighbors</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/neighbors.html#classification">3.4.1. Classification</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/neighbors.html#regression">3.4.2. Regression</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/neighbors.html#efficient-implementation-the-ball-tree">3.4.3. Efficient implementation: the ball tree</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/feature_selection.html">3.5. Feature selection</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/feature_selection.html#univariate-feature-selection">3.5.1. Univariate feature selection</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/feature_selection.html#feature-scoring-functions">3.5.1.1. Feature scoring functions</a><ul> <li class="toctree-l5"><a class="reference internal" href="modules/feature_selection.html#for-classification">3.5.1.1.1. For classification</a></li> <li class="toctree-l5"><a class="reference internal" href="modules/feature_selection.html#for-regression">3.5.1.1.2. For regression</a></li> </ul> </li> </ul> </li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/gaussian_process.html">3.6. Gaussian Processes</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/gaussian_process.html#an-introductory-regression-example">3.6.1. An introductory regression example</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/gaussian_process.html#mathematical-formulation">3.6.2. Mathematical formulation</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/gaussian_process.html#the-initial-assumption">3.6.2.1. The initial assumption</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/gaussian_process.html#the-best-linear-unbiased-prediction-blup">3.6.2.2. The best linear unbiased prediction (BLUP)</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/gaussian_process.html#the-empirical-best-linear-unbiased-predictor-eblup">3.6.2.3. The empirical best linear unbiased predictor (EBLUP)</a></li> </ul> </li> <li class="toctree-l3"><a class="reference internal" href="modules/gaussian_process.html#correlation-models">3.6.3. Correlation Models</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/gaussian_process.html#regression-models">3.6.4. Regression Models</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/gaussian_process.html#implementation-details">3.6.5. Implementation details</a></li> </ul> </li> </ul> </li> <li class="toctree-l1"><a class="reference internal" href="unsupervised_learning.html">4. Unsupervised learning</a><ul> <li class="toctree-l2"><a class="reference internal" href="modules/mixture.html">4.1. Gaussian mixture models</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/mixture.html#gmm-classifier">4.1.1. GMM classifier</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/clustering.html">4.2. Clustering</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/clustering.html#affinity-propagation">4.2.1. Affinity propagation</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/clustering.html#mean-shift">4.2.2. Mean Shift</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/clustering.html#k-means">4.2.3. K-means</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/clustering.html#spectral-clustering">4.2.4. Spectral clustering</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/decompositions.html">4.3. Decomposing signals in components (matrix factorization problems)</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/decompositions.html#principal-component-analysis-pca">4.3.1. Principal component analysis (PCA)</a></li> <li class="toctree-l3"><a class="reference internal" href="modules/decompositions.html#independent-component-analysis-ica">4.3.2. Independent component analysis (ICA)</a></li> </ul> </li> </ul> </li> <li class="toctree-l1"><a class="reference internal" href="model_selection.html">5. Model Selection</a><ul> <li class="toctree-l2"><a class="reference internal" href="modules/cross_validation.html">5.1. Cross-Validation</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/cross_validation.html#examples">5.1.1. Examples</a><ul> <li class="toctree-l4"><a class="reference internal" href="modules/cross_validation.html#leave-one-out-loo">5.1.1.1. Leave-One-Out - LOO</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/cross_validation.html#leave-p-out-lpo">5.1.1.2. Leave-P-Out - LPO</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/cross_validation.html#k-fold">5.1.1.3. K-fold</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/cross_validation.html#stratified-k-fold">5.1.1.4. Stratified K-Fold</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/cross_validation.html#leave-one-label-out-lolo">5.1.1.5. Leave-One-Label-Out - LOLO</a></li> <li class="toctree-l4"><a class="reference internal" href="modules/cross_validation.html#leave-p-label-out">5.1.1.6. Leave-P-Label-Out</a></li> </ul> </li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/grid_search.html">5.2. Grid Search</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/grid_search.html#examples">5.2.1. Examples</a></li> </ul> </li> </ul> </li> <li class="toctree-l1"><a class="reference internal" href="modules/classes.html">6. Class Reference</a><ul> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#support-vector-machines">6.1. Support Vector Machines</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/classes.html#for-sparse-data">6.1.1. For sparse data</a><ul class="simple"> </ul> </li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#generalized-linear-models">6.2. Generalized Linear Models</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/classes.html#id1">6.2.1. For sparse data</a><ul class="simple"> </ul> </li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#bayesian-regression">6.3. Bayesian Regression</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#naive-bayes">6.4. Naive Bayes</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#nearest-neighbors">6.5. Nearest Neighbors</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#gaussian-mixture-models">6.6. Gaussian Mixture Models</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#hidden-markov-models">6.7. Hidden Markov Models</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#clustering">6.8. Clustering</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#covariance-estimators">6.9. Covariance Estimators</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#signal-decomposition">6.10. Signal Decomposition</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#cross-validation">6.11. Cross Validation</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#grid-search">6.12. Grid Search</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#feature-selection">6.13. Feature Selection</a><ul class="simple"> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#feature-extraction">6.14. Feature Extraction</a><ul> <li class="toctree-l3"><a class="reference internal" href="modules/classes.html#id2">6.14.1. For sparse data</a><ul class="simple"> </ul> </li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="modules/classes.html#pipeline">6.15. Pipeline</a><ul class="simple"> </ul> </li> </ul> </li> </ul> </div> </div> </div> </div> </div> <div class="clearer"></div> </div> </div> <div class="footer"> <p style="text-align: center">This documentation is relative to scikits.learn version 0.6.0<p> © 2010, scikits.learn developers (BSD Lincense). Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.0.5. Design by <a href="http://webylimonada.com">Web y Limonada</a>. </div> </body> </html>