## What changes were proposed in this pull request?
Made DataFrame-based API primary
* Spark doc menu bar and other places now link to ml-guide.html, not mllib-guide.html
* mllib-guide.html keeps RDD-specific list of features, with a link at the top redirecting people to ml-guide.html
* ml-guide.html includes a "maintenance mode" announcement about the RDD-based API
* **Reviewers: please check this carefully**
* (minor) Titles for DF API no longer include "- spark.ml" suffix. Titles for RDD API have "- RDD-based API" suffix
* Moved migration guide to ml-guide from mllib-guide
* Also moved past guides from mllib-migration-guides to ml-migration-guides, with a redirect link on mllib-migration-guides
* **Reviewers**: I did not change any of the content of the migration guides.
Reorganized DataFrame-based guide:
* ml-guide.html mimics the old mllib-guide.html page in terms of content: overview, migration guide, etc.
* Moved Pipeline description into ml-pipeline.html and moved tuning into ml-tuning.html
* **Reviewers**: I did not change the content of these guides, except some intro text.
* Sidebar remains the same, but with pipeline and tuning sections added
Other:
* ml-classification-regression.html: Moved text about linear methods to new section in page
## How was this patch tested?
Generated docs locally
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#14213 from jkbradley/ml-guide-2.0.
This PR adds the breaking changes from [SPARK-14810](https://issues.apache.org/jira/browse/SPARK-14810) to the migration guide.
## How was this patch tested?
Built docs locally.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#13924 from MLnick/SPARK-15643-migration-guide.
## What changes were proposed in this pull request?
Update ```spark.ml``` and ```spark.mllib``` migration guide from 1.6 to 2.0.
## How was this patch tested?
Docs update, no tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#13378 from yanboliang/spark-13448.
This documents the implementation of ALS in `spark.ml` with example code in scala, java and python.
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#10411 from BenFradet/SPARK-12247.
No known breaking changes, but some deprecations and changes of behavior.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#10235 from jkbradley/mllib-guide-update-1.6.
This PR includes only an example code in order to finish it quickly.
I'll send another PR for the docs soon.
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#9952 from yu-iskw/SPARK-6518.
Replaces a number of occurences of `MLlib` in the documentation that were meant to refer to the `spark.mllib` package instead. It should clarify for new users the difference between `spark.mllib` (the package) and MLlib (the umbrella project for ML in spark).
It also removes some files that I forgot to delete with #10207
Author: Timothy Hunter <timhunter@databricks.com>
Closes#10234 from thunterdb/12212.
jira: https://issues.apache.org/jira/browse/SPARK-11689
Add simple user guide for LDA under spark.ml and example code under examples/. Use include_example to include example code in the user guide markdown. Check SPARK-11606 for instructions.
Original PR is reverted due to document build error. https://github.com/apache/spark/pull/9722
mengxr feynmanliang yinxusen Sorry for the troubling.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#9974 from hhbyyh/ldaMLExample.
jira: https://issues.apache.org/jira/browse/SPARK-11689
Add simple user guide for LDA under spark.ml and example code under examples/. Use include_example to include example code in the user guide markdown. Check SPARK-11606 for instructions.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#9722 from hhbyyh/ldaMLExample.
Various ML guide cleanups.
* ml-guide.md: Make it easier to access the algorithm-specific guides.
* LDA user guide: EM often begins with useless topics, but running longer generally improves them dramatically. E.g., 10 iterations on a Wikipedia dataset produces useless topics, but 50 iterations produces very meaningful topics.
* mllib-feature-extraction.html#elementwiseproduct: “w” parameter should be “scalingVec”
* Clean up Binarizer user guide a little.
* Document in Pipeline that users should not put an instance into the Pipeline in more than 1 place.
* spark.ml Word2Vec user guide: clean up grammar/writing
* Chi Sq Feature Selector docs: Improve text in doc.
CC: mengxr feynmanliang
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8752 from jkbradley/mlguide-fixes-1.5.
* replace `ML Dataset` by `DataFrame` to unify the abstraction
* ML algorithms -> pipeline components to describe the main concept
* remove Scala API doc links from the main guide
* `Section Title` -> `Section tile` to be consistent with other section titles in MLlib guide
* modified lines break at 100 chars or periods
jkbradley feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8517 from mengxr/SPARK-10348.
This PR updates the MLlib user guide and adds migration guide for 1.4->1.5.
* merge migration guide for `spark.mllib` and `spark.ml` packages
* remove dependency section from `spark.ml` guide
* move the paragraph about `spark.mllib` and `spark.ml` to the top and recommend `spark.ml`
* move Sam's talk to footnote to make the section focus on dependencies
Minor changes to code examples and other wording will be in a separate PR.
jkbradley srowen feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8498 from mengxr/SPARK-9671.
New user guide section ml-decision-tree.md, including code examples.
I have run all examples, including the Java ones.
CC: manishamde yanboliang mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8244 from jkbradley/ml-dt-docs.
Adds user guide for `PrefixSpan`, including Scala and Java example code.
mengxr zhangjiajin
Author: Feynman Liang <fliang@databricks.com>
Closes#8253 from feynmanliang/SPARK-9898.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#7655 from sethah/Working_on_6129 and squashes the following commits:
253db2d [sethah] removed number formatting from example code
b769cab [sethah] rewording threshold section
d5dad4d [sethah] adding some explanations of concepts to the eval metrics user guide
3a61ff9 [sethah] Removing unnecessary latex commands from metrics guide
c9dd058 [sethah] Cleaning up and formatting metrics user guide section
6f31c21 [sethah] All example code for metrics section done
98813fe [sethah] Most java and python example code added. Further latex formatting
53a24fc [sethah] Adding documentations of metrics for ML algorithms to user guide
Reorganized docs a bit. Added migration guides.
**Q**: Do we want to say more for the 1.3 -> 1.4 migration guide for ```spark.ml```? It would be a lot.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6897 from jkbradley/ml-guide-1.4 and squashes the following commits:
4bf26d6 [Joseph K. Bradley] tiny fix
8085067 [Joseph K. Bradley] fixed spacing/layout issues in ml guide from previous commit in this PR
6cd5c78 [Joseph K. Bradley] Updated MLlib programming guide for release 1.4
As discussed in the RC3 vote thread, we should mention the change of objective in linear regression in the migration guide. srowen
Author: Xiangrui Meng <meng@databricks.com>
Closes#4978 from mengxr/SPARK-6278 and squashes the following commits:
fb3bbe6 [Xiangrui Meng] mention regularization parameter
bfd6cff [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-6278
375fd09 [Xiangrui Meng] address Sean's comments
f87ae71 [Xiangrui Meng] mention step size change
The issue is discussed in https://issues.apache.org/jira/browse/SPARK-5669. Replacing all JBLAS usage by netlib-java gives us a simpler dependency tree and less license issues to worry about. I didn't touch the test scope in this PR. The user guide is not modified to avoid merge conflicts with branch-1.3. srowen ankurdave pwendell
Author: Xiangrui Meng <meng@databricks.com>
Closes#4699 from mengxr/SPARK-5814 and squashes the following commits:
48635c6 [Xiangrui Meng] move netlib-java version to parent pom
ca21c74 [Xiangrui Meng] remove jblas from ml-guide
5f7767a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5814
c5c4183 [Xiangrui Meng] merge master
0f20cad [Xiangrui Meng] add mima excludes
e53e9f4 [Xiangrui Meng] remove jblas from mllib runtime
ceaa14d [Xiangrui Meng] replace jblas by netlib-java in graphx
fa7c2ca [Xiangrui Meng] move jblas to test scope
For SPARK-5867:
* The spark.ml programming guide needs to be updated to use the new SQL DataFrame API instead of the old SchemaRDD API.
* It should also include Python examples now.
For SPARK-5892:
* Fix Python docs
* Various other cleanups
BTW, I accidentally merged this with master. If you want to compile it on your own, use this branch which is based on spark/branch-1.3 and cherry-picks the commits from this PR: [https://github.com/jkbradley/spark/tree/doc-review-1.3-check]
CC: mengxr (ML), davies (Python docs)
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#4675 from jkbradley/doc-review-1.3 and squashes the following commits:
f191bb0 [Joseph K. Bradley] small cleanups
e786efa [Joseph K. Bradley] small doc corrections
6b1ab4a [Joseph K. Bradley] fixed python lint test
946affa [Joseph K. Bradley] Added sample data for ml.MovieLensALS example. Changed spark.ml Java examples to use DataFrames API instead of sql()
da81558 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into doc-review-1.3
629dbf5 [Joseph K. Bradley] Updated based on code review: * made new page for old migration guides * small fixes * moved inherit_doc in python
b9df7c4 [Joseph K. Bradley] Small cleanups: toDF to toDF(), adding s for string interpolation
34b067f [Joseph K. Bradley] small doc correction
da16aef [Joseph K. Bradley] Fixed python mllib docs
8cce91c [Joseph K. Bradley] GMM: removed old imports, added some doc
695f3f6 [Joseph K. Bradley] partly done trying to fix inherit_doc for class hierarchies in python docs
a72c018 [Joseph K. Bradley] made ChiSqTestResult appear in python docs
b05a80d [Joseph K. Bradley] organize imports. doc cleanups
e572827 [Joseph K. Bradley] updated programming guide for ml and mllib
The API is still not very Java-friendly because `Array[Item]` in `freqItemsets` is recognized as `Object` in Java. We might want to define a case class to wrap the return pair to make it Java friendly.
Author: Xiangrui Meng <meng@databricks.com>
Closes#4661 from mengxr/SPARK-5519 and squashes the following commits:
58ccc25 [Xiangrui Meng] add user guide with example code for fp-growth
User guide for isotonic regression added to docs/mllib-regression.md including code examples for Scala and Java.
Author: martinzapletal <zapletal-martin@email.cz>
Closes#4536 from zapletal-martin/SPARK-5502 and squashes the following commits:
67fe773 [martinzapletal] SPARK-5502 reworded model prediction rules to use more general language rather than the code/implementation specific terms
80bd4c3 [martinzapletal] SPARK-5502 created docs page for isotonic regression, added links to the page, updated data and examples
7d8136e [martinzapletal] SPARK-5502 Added documentation for Isotonic regression including examples for Scala and Java
504b5c3 [martinzapletal] SPARK-5502 Added documentation for Isotonic regression including examples for Scala and Java
Put example code close to the algorithm description.
Author: Xiangrui Meng <meng@databricks.com>
Closes#4598 from mengxr/SPARK-5806 and squashes the following commits:
a137872 [Xiangrui Meng] re-organize sections in mllib-clustering.md
I am the author of netlib-java and I found this documentation to be out of date. Some main points:
1. Breeze has not depended on jBLAS for some time
2. netlib-java provides a pure JVM implementation as the fallback (the original docs did not appear to be aware of this, claiming that gfortran was necessary)
3. The licensing issue is not just about LGPL: optimised natives have proprietary licenses. Building with the LGPL flag turned on really doesn't help you get past this.
4. I really think it's best to direct people to my detailed setup guide instead of trying to compress it into one sentence. It is different for each architecture, each OS, and for each backend.
I hope this helps to clear things up 😄
Author: Sam Halliday <sam.halliday@Gmail.com>
Author: Sam Halliday <sam.halliday@gmail.com>
Closes#4448 from fommil/patch-1 and squashes the following commits:
18cda11 [Sam Halliday] remove link to skillsmatters at request of @mengxr
a35e4a9 [Sam Halliday] reword netlib-java/breeze docs
Simple description and code samples (and sample data) for GaussianMixture
Author: Travis Galoppo <tjg2107@columbia.edu>
Closes#4401 from tgaloppo/spark-5013 and squashes the following commits:
c9ff9a5 [Travis Galoppo] Fixed link in mllib-clustering.md Added Gaussian mixture and power iteration as available clustering techniques in mllib-guide
2368690 [Travis Galoppo] Minor fixes
3eb41fa [Travis Galoppo] [SPARK-5013] Added documentation and sample data file for GaussianMixture
- Add meta description tags on some of the most important doc pages
- Shorten the titles of some pages to have more relevant keywords; for
example there's no reason to have "Spark SQL Programming Guide - Spark
1.2.0 documentation", we can just say "Spark SQL - Spark 1.2.0
documentation".
Author: Matei Zaharia <matei@databricks.com>
Closes#4381 from mateiz/docs-seo and squashes the following commits:
4940563 [Matei Zaharia] [SPARK-5608] Improve SEO of Spark documentation pages
The current statement in the user guide may deliver confusing messages to users. spark.ml contains high-level APIs for building ML pipelines. But it doesn't mean that spark.mllib is being deprecated.
First of all, the pipeline API is in its alpha stage and we need to see more use cases from the community to stabilizes it, which may take several releases. Secondly, the components in spark.ml are simple wrappers over spark.mllib implementations. Neither the APIs or the implementations from spark.mllib are being deprecated. We expect users use spark.ml pipeline APIs to build their ML pipelines, but we will keep supporting and adding features to spark.mllib. For example, there are many features in review at https://spark-prs.appspot.com/#mllib. So users should be comfortable with using spark.mllib features and expect more coming. The user guide needs to be updated to make the message clear.
Author: Xiangrui Meng <meng@databricks.com>
Closes#4052 from mengxr/SPARK-5254 and squashes the following commits:
6d5f1d3 [Xiangrui Meng] typo
0cc935b [Xiangrui Meng] update user guide to position spark.ml better
Documentation:
* Added ml-guide.md, linked from mllib-guide.md
* Updated mllib-guide.md with small section pointing to ml-guide.md
Examples:
* CrossValidatorExample
* SimpleParamsExample
* (I copied these + the SimpleTextClassificationPipeline example into the ml-guide.md)
Bug fixes:
* PipelineModel: did not use ParamMaps correctly
* UnaryTransformer: issues with TypeTag serialization (Thanks to mengxr for that fix!)
CC: mengxr shivaram etrain Documentation for Pipelines: I know the docs are not complete, but the goal is to have enough to let interested people get started using spark.ml and to add more docs once the package is more established/complete.
Author: Joseph K. Bradley <joseph@databricks.com>
Author: jkbradley <joseph.kurata.bradley@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#3588 from jkbradley/ml-package-docs and squashes the following commits:
d393b5c [Joseph K. Bradley] fixed bug in Pipeline (typo from last commit). updated examples for CV and Params for spark.ml
c38469c [Joseph K. Bradley] Updated ml-guide with CV examples
99f88c2 [Joseph K. Bradley] Fixed bug in PipelineModel.transform* with usage of params. Updated CrossValidatorExample to use more training examples so it is less likely to get a 0-size fold.
ea34dc6 [jkbradley] Merge pull request #4 from mengxr/ml-package-docs
3b83ec0 [Xiangrui Meng] replace TypeTag with explicit datatype
41ad9b1 [Joseph K. Bradley] Added examples for spark.ml: SimpleParamsExample + Java version, CrossValidatorExample + Java version. CrossValidatorExample not working yet. Added programming guide for spark.ml, but need to add CrossValidatorExample to it once CrossValidatorExample works.
Major changes:
* Added programming guide sections for tree ensembles
* Added examples for tree ensembles
* Updated DecisionTree programming guide with more info on parameters
* **API change**: Standardized the tree parameter for the number of classes (for classification)
Minor changes:
* Updated decision tree documentation
* Updated existing tree and tree ensemble examples
* Use train/test split, and compute test error instead of training error.
* Fixed decision_tree_runner.py to actually use the number of classes it computes from data. (small bug fix)
Note: I know this is a lot of lines, but most is covered by:
* Programming guide sections for gradient boosting and random forests. (The changes are probably best viewed by generating the docs locally.)
* New examples (which were copied from the programming guide)
* The "numClasses" renaming
I have run all examples and relevant unit tests.
CC: mengxr manishamde codedeft
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes#3461 from jkbradley/ensemble-docs and squashes the following commits:
70a75f3 [Joseph K. Bradley] updated forest vs boosting comparison
d1de753 [Joseph K. Bradley] Added note about toString and toDebugString for DecisionTree to migration guide
8e87f8f [Joseph K. Bradley] Combined GBT and RandomForest guides into one ensembles guide
6fab846 [Joseph K. Bradley] small fixes based on review
b9f8576 [Joseph K. Bradley] updated decision tree doc
375204c [Joseph K. Bradley] fixed python style
2b60b6e [Joseph K. Bradley] merged Java RandomForest examples into 1 file. added header. Fixed small bug in same example in the programming guide.
706d332 [Joseph K. Bradley] updated python DT runner to print full model if it is small
c76c823 [Joseph K. Bradley] added migration guide for mllib
abe5ed7 [Joseph K. Bradley] added examples for random forest in Java and Python to examples folder
07fc11d [Joseph K. Bradley] Renamed numClassesForClassification to numClasses everywhere in trees and ensembles. This is a breaking API change, but it was necessary to correct an API inconsistency in Spark 1.1 (where Python DecisionTree used numClasses but Scala used numClassesForClassification).
cdfdfbc [Joseph K. Bradley] added examples for GBT
6372a2b [Joseph K. Bradley] updated decision tree examples to use random split. tested all of them.
ad3e695 [Joseph K. Bradley] added gbt and random forest to programming guide. still need to update their examples
The only updates are in DecisionTree.
CC: mengxr
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes#2146 from jkbradley/mllib-migration and squashes the following commits:
5a1f487 [Joseph K. Bradley] small edit to doc
411d6d9 [Joseph K. Bradley] Added migration guide for v1.0 to v1.1. The only updates are in DecisionTree.
1. renamed mllib-basics to mllib-data-types
1. renamed mllib-stats to mllib-statistics
1. moved random data generation to the bottom of mllib-stats
1. updated toc accordingly
atalwalkar
Author: Xiangrui Meng <meng@databricks.com>
Closes#2151 from mengxr/mllib-doc-1.1 and squashes the following commits:
0bd79f3 [Xiangrui Meng] add mllib-data-types
b64a5d7 [Xiangrui Meng] update the content list of basis statistics in mllib-guide
f625cc2 [Xiangrui Meng] move mllib-basics to mllib-data-types
4d69250 [Xiangrui Meng] move random data generation to the bottom of statistics
e64f3ce [Xiangrui Meng] move mllib-stats.md to mllib-statistics.md
to mention `-Pnetlib-lgpl` option. atalwalkar
Author: Xiangrui Meng <meng@databricks.com>
Closes#2128 from mengxr/mllib-native and squashes the following commits:
4cbba57 [Xiangrui Meng] update mllib dependencies
Though we don't use default argument for methods in RandomRDDs, it is still not easy for Java users to use because the output type is either `RDD[Double]` or `RDD[Vector]`. Java users should expect `JavaDoubleRDD` and `JavaRDD[Vector]`, respectively. We should create dedicated methods for Java users, and allow default arguments in Scala methods in RandomRDDs, to make life easier for both Java and Scala users. This PR also contains documentation for random data generation. brkyvz
Author: Xiangrui Meng <meng@databricks.com>
Closes#2041 from mengxr/stat-doc and squashes the following commits:
fc5eedf [Xiangrui Meng] add missing comma
ffde810 [Xiangrui Meng] address comments
aef6d07 [Xiangrui Meng] add doc for random data generation
b99d94b [Xiangrui Meng] add java-friendly methods to RandomRDDs
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
This is a fairly large PR to clean up and update the docs for 1.0. The major changes are:
* A unified programming guide for all languages replaces language-specific ones and shows language-specific info in tabs
* New programming guide sections on key-value pairs, unit testing, input formats beyond text, migrating from 0.9, and passing functions to Spark
* Spark-submit guide moved to a separate page and expanded slightly
* Various cleanups of the menu system, security docs, and others
* Updated look of title bar to differentiate the docs from previous Spark versions
You can find the updated docs at http://people.apache.org/~matei/1.0-docs/_site/ and in particular http://people.apache.org/~matei/1.0-docs/_site/programming-guide.html.
Author: Matei Zaharia <matei@databricks.com>
Closes#896 from mateiz/1.0-docs and squashes the following commits:
03e6853 [Matei Zaharia] Some tweaks to configuration and YARN docs
0779508 [Matei Zaharia] tweak
ef671d4 [Matei Zaharia] Keep frames in JavaDoc links, and other small tweaks
1bf4112 [Matei Zaharia] Review comments
4414f88 [Matei Zaharia] tweaks
d04e979 [Matei Zaharia] Fix some old links to Java guide
a34ed33 [Matei Zaharia] tweak
541bb3b [Matei Zaharia] miscellaneous changes
fcefdec [Matei Zaharia] Moved submitting apps to separate doc
61d72b4 [Matei Zaharia] stuff
181f217 [Matei Zaharia] migration guide, remove old language guides
e11a0da [Matei Zaharia] Add more API functions
6a030a9 [Matei Zaharia] tweaks
8db0ae3 [Matei Zaharia] Added key-value pairs section
318d2c9 [Matei Zaharia] tweaks
1c81477 [Matei Zaharia] New section on basics and function syntax
e38f559 [Matei Zaharia] Actually added programming guide to Git
a33d6fe [Matei Zaharia] First pass at updating programming guide to support all languages, plus other tweaks throughout
3b6a876 [Matei Zaharia] More CSS tweaks
01ec8bf [Matei Zaharia] More CSS tweaks
e6d252e [Matei Zaharia] Change color of doc title bar to differentiate from 0.9.0
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
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
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
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
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
Currently it requires NumPy 1.7 due to using the copyto method (http://docs.scipy.org/doc/numpy/reference/generated/numpy.copyto.html) for extracting data out of an array.
Replace it with a fallback
Author: Sandeep <sandeep@techaddict.me>
Closes#391 from techaddict/1426 and squashes the following commits:
d365962 [Sandeep] SPARK-1426: Make MLlib work with NumPy versions older than 1.7 Currently it requires NumPy 1.7 due to using the copyto method (http://docs.scipy.org/doc/numpy/reference/generated/numpy.copyto.html) for extracting data out of an array. Replace it with a fallback
The reason it wasn't working was passing a bytearray to stream.write(), which is not supported in Python 2.6 but is in 2.7. (This array came from NumPy when we converted data to send it over to Java). Now we just convert those bytearrays to strings of bytes, which preserves nonprintable characters as well.
Author: Matei Zaharia <matei@databricks.com>
Closes#335 from mateiz/mllib-python-2.6 and squashes the following commits:
f26c59f [Matei Zaharia] Update docs to no longer say we need Python 2.7
a84d6af [Matei Zaharia] SPARK-1421. Make MLlib work on Python 2.6
# Principal Component Analysis
Computes the top k principal component coefficients for the m-by-n data matrix X. Rows of X correspond to observations and columns correspond to variables. The coefficient matrix is n-by-k. Each column of the coefficients return matrix contains coefficients for one principal component, and the columns are in descending order of component variance. This function centers the data and uses the singular value decomposition (SVD) algorithm.
## Testing
Tests included:
* All principal components
* Only top k principal components
* Dense SVD tests
* Dense/sparse matrix tests
The results are tested against MATLAB's pca: http://www.mathworks.com/help/stats/pca.html
## Documentation
Added to mllib-guide.md
## Example Usage
Added to examples directory under SparkPCA.scala
Author: Reza Zadeh <rizlar@gmail.com>
Closes#88 from rezazadeh/sparkpca and squashes the following commits:
e298700 [Reza Zadeh] reformat using IDE
3f23271 [Reza Zadeh] documentation and cleanup
b025ab2 [Reza Zadeh] documentation
e2667d4 [Reza Zadeh] assertMatrixApproximatelyEquals
3787bb4 [Reza Zadeh] stylin
c6ecc1f [Reza Zadeh] docs
aa2bbcb [Reza Zadeh] rename sparseToTallSkinnyDense
56975b0 [Reza Zadeh] docs
2df9bde [Reza Zadeh] docs update
8fb0015 [Reza Zadeh] rcond documentation
dbf7797 [Reza Zadeh] correct argument number
a9f1f62 [Reza Zadeh] documentation
4ce6caa [Reza Zadeh] style changes
9a56a02 [Reza Zadeh] use rcond relative to larget svalue
120f796 [Reza Zadeh] housekeeping
156ff78 [Reza Zadeh] string comprehension
2e1cf43 [Reza Zadeh] rename rcond
ea223a6 [Reza Zadeh] many style changes
f4002d7 [Reza Zadeh] more docs
bd53c7a [Reza Zadeh] proper accumulator
a8b5ecf [Reza Zadeh] Don't use for loops
0dc7980 [Reza Zadeh] filter zeros in sparse
6115610 [Reza Zadeh] More documentation
36d51e8 [Reza Zadeh] use JBLAS for UVS^-1 computation
bc4599f [Reza Zadeh] configurable rcond
86f7515 [Reza Zadeh] compute per parition, use while
09726b3 [Reza Zadeh] more style changes
4195e69 [Reza Zadeh] private, accumulator
17002be [Reza Zadeh] style changes
4ba7471 [Reza Zadeh] style change
f4982e6 [Reza Zadeh] Use dense matrix in example
2828d28 [Reza Zadeh] optimizations: normalize once, use inplace ops
72c9fa1 [Reza Zadeh] rename DenseMatrix to TallSkinnyDenseMatrix, lean
f807be9 [Reza Zadeh] fix typo
2d7ccde [Reza Zadeh] Array interface for dense svd and pca
cd290fa [Reza Zadeh] provide RDD[Array[Double]] support
398d123 [Reza Zadeh] style change
55abbfa [Reza Zadeh] docs fix
ef29644 [Reza Zadeh] bad chnage undo
472566e [Reza Zadeh] all files from old pr
555168f [Reza Zadeh] initial files
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