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* Streaming KMeans [MLLIB][SPARK-3254]freeman2014-10-311-1/+95
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This adds a Streaming KMeans algorithm to MLlib. It uses an update rule that generalizes the mini-batch KMeans update to incorporate a decay factor, which allows past data to be forgotten. The decay factor can be specified explicitly, or via a more intuitive "fractional decay" setting, in units of either data points or batches. The PR includes: - StreamingKMeans algorithm with decay factor settings - Usage example - Additions to documentation clustering page - Unit tests of basic behavior and decay behaviors tdas mengxr rezazadeh Author: freeman <the.freeman.lab@gmail.com> Author: Jeremy Freeman <the.freeman.lab@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #2942 from freeman-lab/streaming-kmeans and squashes the following commits: b2e5b4a [freeman] Fixes to docs / examples 078617c [Jeremy Freeman] Merge pull request #1 from mengxr/SPARK-3254 2e682c0 [Xiangrui Meng] take discount on previous weights; use BLAS; detect dying clusters 0411bf5 [freeman] Change decay parameterization 9f7aea9 [freeman] Style fixes 374a706 [freeman] Formatting ad9bdc2 [freeman] Use labeled points and predictOnValues in examples 77dbd3f [freeman] Make initialization check an assertion 9cfc301 [freeman] Make random seed an argument 44050a9 [freeman] Simpler constructor c7050d5 [freeman] Fix spacing 2899623 [freeman] Use pattern matching for clarity a4a316b [freeman] Use collect 1472ec5 [freeman] Doc formatting ea22ec8 [freeman] Fix imports 2086bdc [freeman] Log cluster center updates ea9877c [freeman] More documentation 9facbe3 [freeman] Bug fix 5db7074 [freeman] Example usage for StreamingKMeans f33684b [freeman] Add explanation and example to docs b5b5f8d [freeman] Add better documentation a0fd790 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans 9fd9c15 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans b93350f [freeman] Streaming KMeans with decay
* SPARK-1307 [DOCS] Don't use term 'standalone' to refer to a Spark ApplicationSean Owen2014-10-141-7/+7
| | | | | | | | | | | | HT to Diana, just proposing an implementation of her suggestion, which I rather agreed with. Is there a second/third for the motion? Refer to "self-contained" rather than "standalone" apps to avoid confusion with standalone deployment mode. And fix placement of reference to this in MLlib docs. Author: Sean Owen <sowen@cloudera.com> Closes #2787 from srowen/SPARK-1307 and squashes the following commits: b5b82e2 [Sean Owen] Refer to "self-contained" rather than "standalone" apps to avoid confusion with standalone deployment mode. And fix placement of reference to this in MLlib docs.
* [SPARK-1484][MLLIB] Warn when running an iterative algorithm on uncached data.Aaron Staple2014-09-251-1/+2
| | | | | | | | | | | | | | | | | | | Add warnings to KMeans, GeneralizedLinearAlgorithm, and computeSVD when called with input data that is not cached. KMeans is implemented iteratively, and I believe that GeneralizedLinearAlgorithm’s current optimizers are iterative and its future optimizers are also likely to be iterative. RowMatrix’s computeSVD is iterative against an RDD when run in DistARPACK mode. ALS and DecisionTree are iterative as well, but they implement RDD caching internally so do not require a warning. I added a warning to GeneralizedLinearAlgorithm rather than inside its optimizers, where the iteration actually occurs, because internally GeneralizedLinearAlgorithm maps its input data to an uncached RDD before passing it to an optimizer. (In other words, the warning would be printed for every GeneralizedLinearAlgorithm run, regardless of whether its input is cached, if the warning were in GradientDescent or other optimizer.) I assume that use of an uncached RDD by GeneralizedLinearAlgorithm is intentional, and that the mapping there (adding label, intercepts and scaling) is a lightweight operation. Arguably a user calling an optimizer such as GradientDescent will be knowledgable enough to cache their data without needing a log warning, so lack of a warning in the optimizers may be ok. Some of the documentation examples making use of these iterative algorithms did not cache their training RDDs (while others did). I updated the examples to always cache. I also fixed some (unrelated) minor errors in the documentation examples. Author: Aaron Staple <aaron.staple@gmail.com> Closes #2347 from staple/SPARK-1484 and squashes the following commits: bd49701 [Aaron Staple] Address review comments. ab2d4a4 [Aaron Staple] Disable warnings on python code path. a7a0f99 [Aaron Staple] Change code comments per review comments. 7cca1dc [Aaron Staple] Change warning message text. c77e939 [Aaron Staple] [SPARK-1484][MLLIB] Warn when running an iterative algorithm on uncached data. 3b6c511 [Aaron Staple] Minor doc example fixes.
* SPARK-2830 [MLlib]: re-organize mllib documentationAmeet Talwalkar2014-08-121-7/+8
| | | | | | | | | | | | 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-1945][MLLIB] Documentation Improvements for Spark 1.0Michael Giannakopoulos2014-07-201-1/+48
| | | | | | | | | | | | | | | | | | | | | | Standalone application examples are added to 'mllib-linear-methods.md' file written in Java. This commit is related to the issue [Add full Java Examples in MLlib docs](https://issues.apache.org/jira/browse/SPARK-1945). Also I changed the name of the sigmoid function from 'logit' to 'f'. This is because the logit function is the inverse of sigmoid. Thanks, Michael Author: Michael Giannakopoulos <miccagiann@gmail.com> Closes #1311 from miccagiann/master and squashes the following commits: 8ffe5ab [Michael Giannakopoulos] Update code so as to comply with code standards. f7ad5cc [Michael Giannakopoulos] Merge remote-tracking branch 'upstream/master' 38d92c7 [Michael Giannakopoulos] Adding PCA, SVD and LBFGS examples in Java. Performing minor updates in the already committed examples so as to eradicate the call of 'productElement' function whenever is possible. cc0a089 [Michael Giannakopoulos] Modyfied Java examples so as to comply with coding standards. b1141b2 [Michael Giannakopoulos] Added Java examples for Clustering and Collaborative Filtering [mllib-clustering.md & mllib-collaborative-filtering.md]. 837f7a8 [Michael Giannakopoulos] Merge remote-tracking branch 'upstream/master' 15f0eb4 [Michael Giannakopoulos] Java examples included in 'mllib-linear-methods.md' file.
* SPARK-2363. Clean MLlib's sample data filesSean Owen2014-07-131-2/+2
| | | | | | | | | | | | | | | | (Just made a PR for this, mengxr was the reporter of:) MLlib has sample data under serveral folders: 1) data/mllib 2) data/ 3) mllib/data/* Per previous discussion with Matei Zaharia, we want to put them under `data/mllib` and clean outdated files. Author: Sean Owen <sowen@cloudera.com> Closes #1394 from srowen/SPARK-2363 and squashes the following commits: 54313dd [Sean Owen] Move ML example data from /mllib/data/ and /data/ into /data/mllib/
* [WIP][SPARK-1871][MLLIB] Improve MLlib guide for v1.0Xiangrui Meng2014-05-181-2/+3
| | | | | | | | | | | | | | | | | | | | | | | | Some improvements to MLlib guide: 1. [SPARK-1872] Update API links for unidoc. 2. [SPARK-1783] Added `page.displayTitle` to the global layout. If it is defined, use it instead of `page.title` for title display. 3. Add more Java/Python examples. Author: Xiangrui Meng <meng@databricks.com> Closes #816 from mengxr/mllib-doc and squashes the following commits: ec2e407 [Xiangrui Meng] format scala example for ALS cd9f40b [Xiangrui Meng] add a paragraph to summarize distributed matrix types 4617f04 [Xiangrui Meng] add python example to loadLibSVMFile and fix Java example d6509c2 [Xiangrui Meng] [SPARK-1783] update mllib titles 561fdc0 [Xiangrui Meng] add a displayTitle option to global layout 195d06f [Xiangrui Meng] add Java example for summary stats and minor fix 9f1ff89 [Xiangrui Meng] update java api links in mllib-basics 7dad18e [Xiangrui Meng] update java api links in NB 3a0f4a6 [Xiangrui Meng] api/pyspark -> api/python 35bdeb9 [Xiangrui Meng] api/mllib -> api/scala e4afaa8 [Xiangrui Meng] explicity state what might change
* SPARK-1727. Correct small compile errors, typos, and markdown issues in ↵Sean Owen2014-05-061-2/+2
| | | | | | | | | | | | | | | | | | (primarly) MLlib docs While play-testing the Scala and Java code examples in the MLlib docs, I noticed a number of small compile errors, and some typos. This led to finding and fixing a few similar items in other docs. Then in the course of building the site docs to check the result, I found a few small suggestions for the build instructions. I also found a few more formatting and markdown issues uncovered when I accidentally used maruku instead of kramdown. Author: Sean Owen <sowen@cloudera.com> Closes #653 from srowen/SPARK-1727 and squashes the following commits: 6e7c38a [Sean Owen] Final doc updates - one more compile error, and use of mean instead of sum and count 8f5e847 [Sean Owen] Fix markdown syntax issues that maruku flags, even though we use kramdown (but only those that do not affect kramdown's output) 99966a9 [Sean Owen] Update issue tracker URL in docs 23c9ac3 [Sean Owen] Add Scala Naive Bayes example, to use existing example data file (whose format needed a tweak) 8c81982 [Sean Owen] Fix small compile errors and typos across MLlib docs
* [SPARK-1506][MLLIB] Documentation improvements for MLlib 1.0Xiangrui Meng2014-04-221-23/+21
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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 Zaharia2014-04-211-1/+1
| | | | | | | | | | | | | | | | | | | | | | 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 Zaharia2014-04-151-5/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* Merge pull request #552 from martinjaggi/master. Closes #552.Martin Jaggi2014-02-081-0/+106
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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