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authorManish Amde <manish9ue@gmail.com>2014-04-15 11:14:28 -0700
committerPatrick Wendell <pwendell@gmail.com>2014-04-15 11:14:28 -0700
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parent6843d637e72e5262d05cfa2b1935152743f2bd5a (diff)
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Decision Tree documentation for MLlib programming guide
Added documentation for user to use the decision tree algorithms for classification and regression in Spark 1.0 release. Apart from a general review, I need specific input on the following: * I had to move a lot of the existing documentation under the *linear methods* umbrella to accommodate decision trees. I wonder if there is a better way to organize the programming guide given we are so close to the release. * I have not looked closely at pyspark but I am wondering new mllib algorithms are automatically plugged in or do we need to some extra work to call mllib functions from pyspark. I will add to the pyspark examples based upon the advice I get. cc: @mengxr, @hirakendu, @etrain, @atalwalkar Author: Manish Amde <manish9ue@gmail.com> Closes #402 from manishamde/tree_doc and squashes the following commits: 022485a [Manish Amde] more documentation 865826e [Manish Amde] minor: grammar dbb0e5e [Manish Amde] minor improvements to text b9ef6c4 [Manish Amde] basic decision tree code examples 6e297d7 [Manish Amde] added subsections f427e84 [Manish Amde] renaming sections 9c0c4be [Manish Amde] split candidate 6925275 [Manish Amde] impurity and information gain 94fd2f9 [Manish Amde] more reorg b93125c [Manish Amde] more subsection reorg 3ecb2ad [Manish Amde] minor text addition 1537dd3 [Manish Amde] added placeholders and some doc d06511d [Manish Amde] basic skeleton
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@@ -21,6 +21,7 @@ The following links provide a detailed explanation of the methods and usage exam
* Least Squares
* Lasso
* Ridge Regression
+ * Decision Tree (for classification and regression)
* <a href="mllib-clustering.html">Clustering</a>
* k-Means
* <a href="mllib-collaborative-filtering.html">Collaborative Filtering</a>