From d20559b157743981b9c09e286f2aaff8cbefab59 Mon Sep 17 00:00:00 2001 From: "Joseph K. Bradley" Date: Wed, 25 Feb 2015 16:13:17 -0800 Subject: [SPARK-5974] [SPARK-5980] [mllib] [python] [docs] Update ML guide with save/load, Python GBT * Add GradientBoostedTrees Python examples to ML guide * I ran these in the pyspark shell, and they worked. * Add save/load to examples in ML guide * Added note to python docs about predict,transform not working within RDD actions,transformations in some cases (See SPARK-5981) CC: mengxr Author: Joseph K. Bradley Closes #4750 from jkbradley/SPARK-5974 and squashes the following commits: c410e38 [Joseph K. Bradley] Added note to LabeledPoint about attributes bcae18b [Joseph K. Bradley] Added import of models for save/load examples in ml guide. Fixed line length for tree.py, feature.py (but not other ML Pyspark files yet). 6d81c3e [Joseph K. Bradley] completed python GBT examples 9903309 [Joseph K. Bradley] Added note to python docs about predict,transform not working within RDD actions,transformations in some cases c7dfad8 [Joseph K. Bradley] Added model save/load to ML guide. Added GBT examples to ML guide --- docs/mllib-classification-regression.md | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) (limited to 'docs/mllib-classification-regression.md') diff --git a/docs/mllib-classification-regression.md b/docs/mllib-classification-regression.md index 5b9b4dd83b..8e91d62f4a 100644 --- a/docs/mllib-classification-regression.md +++ b/docs/mllib-classification-regression.md @@ -17,13 +17,13 @@ the supported algorithms for each type of problem. - Binary Classificationlinear SVMs, logistic regression, decision trees, naive Bayes + Binary Classificationlinear SVMs, logistic regression, decision trees, random forests, gradient-boosted trees, naive Bayes - Multiclass Classificationdecision trees, naive Bayes + Multiclass Classificationdecision trees, random forests, naive Bayes - Regressionlinear least squares, Lasso, ridge regression, decision trees, isotonic regression + Regressionlinear least squares, Lasso, ridge regression, decision trees, random forests, gradient-boosted trees, isotonic regression @@ -34,5 +34,8 @@ More details for these methods can be found here: * [binary classification (SVMs, logistic regression)](mllib-linear-methods.html#binary-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) + * [random forests](mllib-ensembles.html#random-forests) + * [gradient-boosted trees](mllib-ensembles.html#gradient-boosted-trees-gbts) * [Naive Bayes](mllib-naive-bayes.html) * [Isotonic regression](mllib-isotonic-regression.html) -- cgit v1.2.3