63a5ce75ea
Added logistic regression to the list of Multiclass Classification Supported Methods in the MLlib Classification and Regression documentation, as it was missing. Author: Mike Dusenberry <dusenberrymw@gmail.com> Closes #6357 from dusenberrymw/Add_LR_To_List_Of_Multiclass_Classification_Methods and squashes the following commits: 7918650 [Mike Dusenberry] Updating broken link due to the "Binary Classification" section on the Linear Methods page being renamed to "Classification". 3005dc2 [Mike Dusenberry] Adding logistic regression to the list of Multiclass Classification Supported Methods in the MLlib Classification and Regression documentation, as it was missing.
42 lines
1.7 KiB
Markdown
42 lines
1.7 KiB
Markdown
---
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layout: global
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title: Classification and Regression - MLlib
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displayTitle: <a href="mllib-guide.html">MLlib</a> - Classification and Regression
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---
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MLlib supports various methods for
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[binary classification](http://en.wikipedia.org/wiki/Binary_classification),
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[multiclass
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classification](http://en.wikipedia.org/wiki/Multiclass_classification), and
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[regression analysis](http://en.wikipedia.org/wiki/Regression_analysis). The table below outlines
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the supported algorithms for each type of problem.
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<table class="table">
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<thead>
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<tr><th>Problem Type</th><th>Supported Methods</th></tr>
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</thead>
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<tbody>
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<tr>
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<td>Binary Classification</td><td>linear SVMs, logistic regression, decision trees, random forests, gradient-boosted trees, naive Bayes</td>
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</tr>
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<tr>
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<td>Multiclass Classification</td><td>logistic regression, decision trees, random forests, naive Bayes</td>
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</tr>
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<tr>
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<td>Regression</td><td>linear least squares, Lasso, ridge regression, decision trees, random forests, gradient-boosted trees, isotonic regression</td>
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</tr>
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</tbody>
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</table>
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More details for these methods can be found here:
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* [Linear models](mllib-linear-methods.html)
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* [classification (SVMs, logistic regression)](mllib-linear-methods.html#classification)
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* [linear regression (least squares, Lasso, ridge)](mllib-linear-methods.html#linear-least-squares-lasso-and-ridge-regression)
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* [Decision trees](mllib-decision-tree.html)
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* [Ensembles of decision trees](mllib-ensembles.html)
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* [random forests](mllib-ensembles.html#random-forests)
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* [gradient-boosted trees](mllib-ensembles.html#gradient-boosted-trees-gbts)
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* [Naive Bayes](mllib-naive-bayes.html)
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* [Isotonic regression](mllib-isotonic-regression.html)
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