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| author | Mike Dusenberry <dusenberrymw@gmail.com> | 2015-05-22 18:03:12 -0700 |
|---|---|---|
| committer | Joseph K. Bradley <joseph@databricks.com> | 2015-05-22 18:03:12 -0700 |
| commit | 63a5ce75eac48a297751ac505d70ce4d47daf903 (patch) | |
| tree | 23805e380ba8702ecde77c8f6a0e4d024f202b22 | |
| parent | 8014e1f6bb871d9fd4db74106eb4425d0c1e9dd6 (diff) | |
| download | spark-63a5ce75eac48a297751ac505d70ce4d47daf903.tar.gz spark-63a5ce75eac48a297751ac505d70ce4d47daf903.tar.bz2 spark-63a5ce75eac48a297751ac505d70ce4d47daf903.zip | |
[SPARK-7830] [DOCS] [MLLIB] Adding logistic regression to the list of Multiclass Classification Supported Methods documentation
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.
| -rw-r--r-- | docs/mllib-classification-regression.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/docs/mllib-classification-regression.md b/docs/mllib-classification-regression.md index 8e91d62f4a..0210950b89 100644 --- a/docs/mllib-classification-regression.md +++ b/docs/mllib-classification-regression.md @@ -20,7 +20,7 @@ the supported algorithms for each type of problem. <td>Binary Classification</td><td>linear SVMs, logistic regression, decision trees, random forests, gradient-boosted trees, naive Bayes</td> </tr> <tr> - <td>Multiclass Classification</td><td>decision trees, random forests, naive Bayes</td> + <td>Multiclass Classification</td><td>logistic regression, decision trees, random forests, naive Bayes</td> </tr> <tr> <td>Regression</td><td>linear least squares, Lasso, ridge regression, decision trees, random forests, gradient-boosted trees, isotonic regression</td> @@ -31,7 +31,7 @@ the supported algorithms for each type of problem. More details for these methods can be found here: * [Linear models](mllib-linear-methods.html) - * [binary classification (SVMs, logistic regression)](mllib-linear-methods.html#binary-classification) + * [classification (SVMs, logistic regression)](mllib-linear-methods.html#classification) * [linear regression (least squares, Lasso, ridge)](mllib-linear-methods.html#linear-least-squares-lasso-and-ridge-regression) * [Decision trees](mllib-decision-tree.html) * [Ensembles of decision trees](mllib-ensembles.html) |