From 1c6cf1a5639bf5111324e44d93a8c6462958750a Mon Sep 17 00:00:00 2001 From: Yanbo Liang Date: Tue, 5 Jan 2016 14:24:32 -0800 Subject: [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 Closes #10594 from yanboliang/spark-12570. --- docs/ml-classification-regression.md | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) (limited to 'docs') 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 Vector of length # classes equal to rawPrediction normalized to a multinomial distribution Classification only + + varianceCol + Double + + The biased sample variance of prediction + Regression only + -- cgit v1.2.3