From 1c6cf1a5639bf5111324e44d93a8c6462958750a Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Tue, 5 Jan 2016 14:24:32 -0800
Subject: [PATCH] [SPARK-12570][ML][DOC] DecisionTreeRegressor: provide
variance of prediction: user guide update
Update user guide doc for ```DecisionTreeRegressor``` providing variance of prediction.
cc jkbradley
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #10594 from yanboliang/spark-12570.
---
docs/ml-classification-regression.md | 11 ++++++++++-
1 file changed, 10 insertions(+), 1 deletion(-)
diff --git a/docs/ml-classification-regression.md b/docs/ml-classification-regression.md
index d63438bf74..8ffc997b4b 100644
--- a/docs/ml-classification-regression.md
+++ b/docs/ml-classification-regression.md
@@ -535,7 +535,9 @@ The main differences between this API and the [original MLlib Decision Tree API]
* use of DataFrame metadata to distinguish continuous and categorical features
-The Pipelines API for Decision Trees offers a bit more functionality than the original API. In particular, for classification, users can get the predicted probability of each class (a.k.a. class conditional probabilities).
+The Pipelines API for Decision Trees offers a bit more functionality than the original API.
+In particular, for classification, users can get the predicted probability of each class (a.k.a. class conditional probabilities);
+for regression, users can get the biased sample variance of prediction.
Ensembles of trees (Random Forests and Gradient-Boosted Trees) are described below in the [Tree ensembles section](#tree-ensembles).
@@ -605,6 +607,13 @@ All output columns are optional; to exclude an output column, set its correspond
<td>Vector of length # classes equal to rawPrediction normalized to a multinomial distribution</td>
<td>Classification only</td>
</tr>
+ <tr>
+ <td>varianceCol</td>
+ <td>Double</td>
+ <td></td>
+ <td>The biased sample variance of prediction</td>
+ <td>Regression only</td>
+ </tr>
</tbody>
</table>
--
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