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* SPARK-2830 [MLlib]: re-organize mllib documentationAmeet Talwalkar2014-08-121-0/+37
| | | | | | | | | | | | As per discussions with Xiangrui, I've reorganized and edited the mllib documentation. Author: Ameet Talwalkar <atalwalkar@gmail.com> Closes #1908 from atalwalkar/master and squashes the following commits: fe6938a [Ameet Talwalkar] made xiangruis suggested changes 840028b [Ameet Talwalkar] made xiangruis suggested changes 7ec366a [Ameet Talwalkar] reorganize and edit mllib documentation
* [SPARK-1506][MLLIB] Documentation improvements for MLlib 1.0Xiangrui Meng2014-04-221-568/+0
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Preview: http://54.82.240.23:4000/mllib-guide.html Table of contents: * Basics * Data types * Summary statistics * Classification and regression * linear support vector machine (SVM) * logistic regression * linear linear squares, Lasso, and ridge regression * decision tree * naive Bayes * Collaborative Filtering * alternating least squares (ALS) * Clustering * k-means * Dimensionality reduction * singular value decomposition (SVD) * principal component analysis (PCA) * Optimization * stochastic gradient descent * limited-memory BFGS (L-BFGS) Author: Xiangrui Meng <meng@databricks.com> Closes #422 from mengxr/mllib-doc and squashes the following commits: 944e3a9 [Xiangrui Meng] merge master f9fda28 [Xiangrui Meng] minor 9474065 [Xiangrui Meng] add alpha to ALS examples 928e630 [Xiangrui Meng] initialization_mode -> initializationMode 5bbff49 [Xiangrui Meng] add imports to labeled point examples c17440d [Xiangrui Meng] fix python nb example 28f40dc [Xiangrui Meng] remove localhost:4000 369a4d3 [Xiangrui Meng] Merge branch 'master' into mllib-doc 7dc95cc [Xiangrui Meng] update linear methods 053ad8a [Xiangrui Meng] add links to go back to the main page abbbf7e [Xiangrui Meng] update ALS argument names 648283e [Xiangrui Meng] level down statistics 14e2287 [Xiangrui Meng] add sample libsvm data and use it in guide 8cd2441 [Xiangrui Meng] minor updates 186ab07 [Xiangrui Meng] update section names 6568d65 [Xiangrui Meng] update toc, level up lr and svm 162ee12 [Xiangrui Meng] rename section names 5c1e1b1 [Xiangrui Meng] minor 8aeaba1 [Xiangrui Meng] wrap long lines 6ce6a6f [Xiangrui Meng] add summary statistics to toc 5760045 [Xiangrui Meng] claim beta cc604bf [Xiangrui Meng] remove classification and regression 92747b3 [Xiangrui Meng] make section titles consistent e605dd6 [Xiangrui Meng] add LIBSVM loader f639674 [Xiangrui Meng] add python section to migration guide c82ffb4 [Xiangrui Meng] clean optimization 31660eb [Xiangrui Meng] update linear algebra and stat 0a40837 [Xiangrui Meng] first pass over linear methods 1fc8271 [Xiangrui Meng] update toc 906ed0a [Xiangrui Meng] add a python example to naive bayes 5f0a700 [Xiangrui Meng] update collaborative filtering 656d416 [Xiangrui Meng] update mllib-clustering 86e143a [Xiangrui Meng] remove data types section from main page 8d1a128 [Xiangrui Meng] move part of linear algebra to data types and add Java/Python examples d1b5cbf [Xiangrui Meng] merge master 72e4804 [Xiangrui Meng] one pass over tree guide 64f8995 [Xiangrui Meng] move decision tree guide to a separate file 9fca001 [Xiangrui Meng] add first version of linear algebra guide 53c9552 [Xiangrui Meng] update dependencies f316ec2 [Xiangrui Meng] add migration guide f399f6c [Xiangrui Meng] move linear-algebra to dimensionality-reduction 182460f [Xiangrui Meng] add guide for naive Bayes 137fd1d [Xiangrui Meng] re-organize toc a61e434 [Xiangrui Meng] update mllib's toc
* [SPARK-1439, SPARK-1440] Generate unified Scaladoc across projects and JavadocsMatei Zaharia2014-04-211-7/+7
| | | | | | | | | | | | | | | | | | | | | | I used the sbt-unidoc plugin (https://github.com/sbt/sbt-unidoc) to create a unified Scaladoc of our public packages, and generate Javadocs as well. One limitation is that I haven't found an easy way to exclude packages in the Javadoc; there is a SBT task that identifies Java sources to run javadoc on, but it's been very difficult to modify it from outside to change what is set in the unidoc package. Some SBT-savvy people should help with this. The Javadoc site also lacks package-level descriptions and things like that, so we may want to look into that. We may decide not to post these right now if it's too limited compared to the Scala one. Example of the built doc site: http://people.csail.mit.edu/matei/spark-unified-docs/ Author: Matei Zaharia <matei@databricks.com> This patch had conflicts when merged, resolved by Committer: Patrick Wendell <pwendell@gmail.com> Closes #457 from mateiz/better-docs and squashes the following commits: a63d4a3 [Matei Zaharia] Skip Java/Scala API docs for Python package 5ea1f43 [Matei Zaharia] Fix links to Java classes in Java guide, fix some JS for scrolling to anchors on page load f05abc0 [Matei Zaharia] Don't include java.lang package names 995e992 [Matei Zaharia] Skip internal packages and class names with $ in JavaDoc a14a93c [Matei Zaharia] typo 76ce64d [Matei Zaharia] Add groups to Javadoc index page, and a first package-info.java ed6f994 [Matei Zaharia] Generate JavaDoc as well, add titles, update doc site to use unified docs acb993d [Matei Zaharia] Add Unidoc plugin for the projects we want Unidoced
* [WIP] SPARK-1430: Support sparse data in Python MLlibMatei Zaharia2014-04-151-18/+27
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds a SparseVector class in PySpark and updates all the regression, classification and clustering algorithms and models to support sparse data, similar to MLlib. I chose to add this class because SciPy is quite difficult to install in many environments (more so than NumPy), but I plan to add support for SciPy sparse vectors later too, and make the methods work transparently on objects of either type. On the Scala side, we keep Python sparse vectors sparse and pass them to MLlib. We always return dense vectors from our models. Some to-do items left: - [x] Support SciPy's scipy.sparse matrix objects when SciPy is available. We can easily add a function to convert these to our own SparseVector. - [x] MLlib currently uses a vector with one extra column on the left to represent what we call LabeledPoint in Scala. Do we really want this? It may get annoying once you deal with sparse data since you must add/subtract 1 to each feature index when training. We can remove this API in 1.0 and use tuples for labeling. - [x] Explain how to use these in the Python MLlib docs. CC @mengxr, @joshrosen Author: Matei Zaharia <matei@databricks.com> Closes #341 from mateiz/py-ml-update and squashes the following commits: d52e763 [Matei Zaharia] Remove no-longer-needed slice code and handle review comments ea5a25a [Matei Zaharia] Fix remaining uses of copyto() after merge b9f97a3 [Matei Zaharia] Fix test 1e1bd0f [Matei Zaharia] Add MLlib logistic regression example in Python 88bc01f [Matei Zaharia] Clean up inheritance of LinearModel in Python, and expose its parametrs 37ab747 [Matei Zaharia] Fix some examples and docs due to changes in MLlib API da0f27e [Matei Zaharia] Added a MLlib K-means example and updated docs to discuss sparse data c48e85a [Matei Zaharia] Added some tests for passing lists as input, and added mllib/tests.py to run-tests script. a07ba10 [Matei Zaharia] Fix some typos and calculation of initial weights 74eefe7 [Matei Zaharia] Added LabeledPoint class in Python 889dde8 [Matei Zaharia] Support scipy.sparse matrices in all our algorithms and models ab244d1 [Matei Zaharia] Allow SparseVectors to be initialized using a dict a5d6426 [Matei Zaharia] Add linalg.py to run-tests script 0e7a3d8 [Matei Zaharia] Keep vectors sparse in Java when reading LabeledPoints eaee759 [Matei Zaharia] Update regression, classification and clustering models for sparse data 2abbb44 [Matei Zaharia] Further work to get linear models working with sparse data 154f45d [Matei Zaharia] Update docs, name some magic values 881fef7 [Matei Zaharia] Added a sparse vector in Python and made Java-Python format more compact
* Decision Tree documentation for MLlib programming guideManish Amde2014-04-151-16/+153
| | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* SPARK-1183. Don't use "worker" to mean executorSandy Ryza2014-03-131-2/+2
| | | | | | | | | | | | Author: Sandy Ryza <sandy@cloudera.com> Closes #120 from sryza/sandy-spark-1183 and squashes the following commits: 5066a4a [Sandy Ryza] Remove "worker" in a couple comments 0bd1e46 [Sandy Ryza] Remove --am-class from usage bfc8fe0 [Sandy Ryza] Remove am-class from doc and fix yarn-alpha 607539f [Sandy Ryza] Address review comments 74d087a [Sandy Ryza] SPARK-1183. Don't use "worker" to mean executor
* Merge pull request #566 from martinjaggi/copy-MLlib-d.Martin Jaggi2014-02-091-39/+255
| | | | | | | | | | | | | | | | | | | | | | | | | | | | new MLlib documentation for optimization, regression and classification new documentation with tex formulas, hopefully improving usability and reproducibility of the offered MLlib methods. also did some minor changes in the code for consistency. scala tests pass. this is the rebased branch, i deleted the old PR jira: https://spark-project.atlassian.net/browse/MLLIB-19 Author: Martin Jaggi <m.jaggi@gmail.com> Closes #566 and squashes the following commits: 5f0f31e [Martin Jaggi] line wrap at 100 chars 4e094fb [Martin Jaggi] better description of GradientDescent 1d6965d [Martin Jaggi] remove broken url ea569c3 [Martin Jaggi] telling what updater actually does 964732b [Martin Jaggi] lambda R() in documentation a6c6228 [Martin Jaggi] better comments in SGD code for regression b32224a [Martin Jaggi] new optimization documentation d5dfef7 [Martin Jaggi] new classification and regression documentation b07ead6 [Martin Jaggi] correct scaling for MSE loss ba6158c [Martin Jaggi] use d for the number of features bab2ed2 [Martin Jaggi] renaming LeastSquaresGradient
* Merge pull request #552 from martinjaggi/master. Closes #552.Martin Jaggi2014-02-081-0/+206
tex formulas in the documentation using mathjax. and spliting the MLlib documentation by techniques see jira https://spark-project.atlassian.net/browse/MLLIB-19 and https://github.com/shivaram/spark/compare/mathjax Author: Martin Jaggi <m.jaggi@gmail.com> == Merge branch commits == commit 0364bfabbfc347f917216057a20c39b631842481 Author: Martin Jaggi <m.jaggi@gmail.com> Date: Fri Feb 7 03:19:38 2014 +0100 minor polishing, as suggested by @pwendell commit dcd2142c164b2f602bf472bb152ad55bae82d31a Author: Martin Jaggi <m.jaggi@gmail.com> Date: Thu Feb 6 18:04:26 2014 +0100 enabling inline latex formulas with $.$ same mathjax configuration as used in math.stackexchange.com sample usage in the linear algebra (SVD) documentation commit bbafafd2b497a5acaa03a140bb9de1fbb7d67ffa Author: Martin Jaggi <m.jaggi@gmail.com> Date: Thu Feb 6 17:31:29 2014 +0100 split MLlib documentation by techniques and linked from the main mllib-guide.md site commit d1c5212b93c67436543c2d8ddbbf610fdf0a26eb Author: Martin Jaggi <m.jaggi@gmail.com> Date: Thu Feb 6 16:59:43 2014 +0100 enable mathjax formula in the .md documentation files code by @shivaram commit d73948db0d9bc36296054e79fec5b1a657b4eab4 Author: Martin Jaggi <m.jaggi@gmail.com> Date: Thu Feb 6 16:57:23 2014 +0100 minor update on how to compile the documentation
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