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.
* Adds two new sections to LDA's user guide; one for each optimizer/model
* Documents new features added to LDA (e.g. topXXXperXXX, asymmetric priors, hyperpam optimization)
* Cleans up a TODO and sets a default parameter in LDA code
jkbradley hhbyyh
Author: Feynman Liang <fliang@databricks.com>
Closes#8254 from feynmanliang/SPARK-9888.
Add support for saving and loading LDA both the local and distributed versions.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6948 from MechCoder/lda_save_load and squashes the following commits:
49bcdce [MechCoder] minor style fixes
cc14054 [MechCoder] minor
4587d1d [MechCoder] Minor changes
c753122 [MechCoder] Load and save the model in private methods
2782326 [MechCoder] [SPARK-5989] Model save/load for LDA
This allows Kmeans to be initialized using an existing set of cluster centers provided as a KMeansModel object. This mode of initialization performs a single run.
Author: FlytxtRnD <meethu.mathew@flytxt.com>
Closes#6737 from FlytxtRnD/Kmeans-8018 and squashes the following commits:
94b56df [FlytxtRnD] style correction
ef95ee2 [FlytxtRnD] style correction
c446c58 [FlytxtRnD] documentation and numRuns warning change
06d13ef [FlytxtRnD] numRuns corrected
d12336e [FlytxtRnD] numRuns variable modifications
07f8554 [FlytxtRnD] remove setRuns from setIntialModel
e721dfe [FlytxtRnD] Merge remote-tracking branch 'upstream/master' into Kmeans-8018
242ead1 [FlytxtRnD] corrected == to === in assert
714acb5 [FlytxtRnD] added numRuns
60c8ce2 [FlytxtRnD] ignore runs parameter and initialModel test suite changed
582e6d9 [FlytxtRnD] Merge remote-tracking branch 'upstream/master' into Kmeans-8018
3f5fc8e [FlytxtRnD] test case modified and one runs condition added
cd5dc5c [FlytxtRnD] Merge remote-tracking branch 'upstream/master' into Kmeans-8018
16f1b53 [FlytxtRnD] Merge branch 'Kmeans-8018', remote-tracking branch 'upstream/master' into Kmeans-8018
e9c35d7 [FlytxtRnD] Remove getInitialModel and match cluster count criteria
6959861 [FlytxtRnD] Accept initial cluster centers in KMeans
See the jira https://issues.apache.org/jira/browse/SPARK-5562
Author: Alok Singh <singhal@Aloks-MacBook-Pro.local>
Author: Alok Singh <singhal@aloks-mbp.usca.ibm.com>
Author: Alok Singh <“singhal@us.ibm.com”>
Closes#7064 from aloknsingh/aloknsingh_SPARK-5562 and squashes the following commits:
259a0a7 [Alok Singh] change as per the comments by @jkbradley
be48491 [Alok Singh] [SPARK-5562][MLlib] re-order import in alphabhetical order
c01311b [Alok Singh] [SPARK-5562][MLlib] fix the newline typo
b271c8a [Alok Singh] [SPARK-5562][Mllib] As per github discussion with jkbradley. We would like to simply things.
7c06251 [Alok Singh] [SPARK-5562][MLlib] modified the JavaLDASuite for test passing
c710cb6 [Alok Singh] fix the scala code style to have space after :
2572a08 [Alok Singh] [SPARK-5562][MLlib] change the import xyz._ to the import xyz.{c1, c2} ..
ab55fbf [Alok Singh] [SPARK-5562][MLlib] Change as per Sean Owen's comments https://github.com/apache/spark/pull/7064/files#diff-9236d23975e6f5a5608ffc81dfd79146
9f4f9ea [Alok Singh] [SPARK-5562][MLlib] LDA should handle empty document.
Add Python user guide for PowerIterationClustering
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7155 from yanboliang/spark-8758 and squashes the following commits:
18d803b [Yanbo Liang] address comments
dd29577 [Yanbo Liang] Add Python user guide for PowerIterationClustering
Python bindings for StreamingKMeans
Will change status to MRG once docs, tests and examples are updated.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6499 from MechCoder/spark-4118 and squashes the following commits:
7722d16 [MechCoder] minor style fixes
51052d3 [MechCoder] Doc fixes
2061a76 [MechCoder] Add tests for simultaneous training and prediction Minor style fixes
81482fd [MechCoder] minor
5d9fe61 [MechCoder] predictOn should take into account the latest model
8ab9e89 [MechCoder] Fix Python3 error
a9817df [MechCoder] Better tests and minor fixes
c80e451 [MechCoder] Add ignore_unicode_prefix
ee8ce16 [MechCoder] Update tests, doc and examples
4b1481f [MechCoder] Some changes and tests
d8b066a [MechCoder] [SPARK-4118] [MLlib] [PySpark] Python bindings for StreamingKMeans
jira: https://issues.apache.org/jira/browse/SPARK-8043
I found some issues during testing the save/load examples in markdown Documents, as a part of 1.4 QA plan
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6584 from hhbyyh/naiveDocExample and squashes the following commits:
a01a206 [Yuhao Yang] fix for Gaussian mixture
2fb8b96 [Yuhao Yang] update NaiveBayes and SVM examples in doc
add save load for examples:
KMeansModel
PowerIterationClusteringModel
Word2VecModel
IsotonicRegressionModel
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6498 from hhbyyh/docSaveLoad and squashes the following commits:
7f9f06d [Yuhao Yang] add missing imports
c604cad [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into docSaveLoad
1dd77cc [Yuhao Yang] update document with some missing save/load
jira: https://issues.apache.org/jira/browse/SPARK-7496
Update LDA subsection of clustering section of MLlib programming guide to include OnlineLDA.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6046 from hhbyyh/ldaDocument and squashes the following commits:
4b6fbfa [Yuhao Yang] add online paper and some comparison
fd4c983 [Yuhao Yang] update lda document for optimizers
Should be self explanatory.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#4986 from MechCoder/spark-5987 and squashes the following commits:
7d2cd56 [MechCoder] Iterate over dataframe in a better way
e7a14cb [MechCoder] Minor
33c84f9 [MechCoder] Store as Array[Data] instead of Data[Array]
505bd57 [MechCoder] Rebased over master and used MatrixUDT
7422bb4 [MechCoder] Store sigmas as Array[Double] instead of Array[Array[Double]]
b9794e4 [MechCoder] Minor
cb77095 [MechCoder] [SPARK-5987] Save/load for GaussianMixtureModels
In the previous version, PIC stores clustering assignments as an `RDD[(Long, Int)]`. This is mapped to `RDD<Tuple2<Object, Object>>` in Java and hence Java users have to cast types manually. We should either create a new method called `javaAssignments` that returns `JavaRDD[(java.lang.Long, java.lang.Int)]` or wrap the result pair in a class. I chose the latter approach in this PR. Now assignments are stored as an `RDD[Assignment]`, where `Assignment` is a class with `id` and `cluster`.
Similarly, in FPGrowth, the frequent itemsets are stored as an `RDD[(Array[Item], Long)]`, which is mapped to `RDD<Tuple2<Object, Object>>`. Though we provide a "Java-friendly" method `javaFreqItemsets` that returns `JavaRDD[(Array[Item], java.lang.Long)]`. It doesn't really work because `Array[Item]` is mapped to `Object` in Java. So in this PR I created a class `FreqItemset` to wrap the results. It has `items` and `freq`, as well as a `javaItems` method that returns `List<Item>` in Java.
I'm not certain that the names I chose are proper: `Assignment`/`id`/`cluster` and `FreqItemset`/`items`/`freq`. Please let me know if there are better suggestions.
CC: jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#4695 from mengxr/SPARK-5900 and squashes the following commits:
865b5ca [Xiangrui Meng] make Assignment serializable
cffa96e [Xiangrui Meng] fix test
9c0e590 [Xiangrui Meng] remove unused Tuple2
1b9db3d [Xiangrui Meng] make PIC and FPGrowth Java-friendly
Updated PIC user guide to reflect API changes and added a simple Java example. The API is still not very Java-friendly. I created SPARK-5990 for this issue.
Author: Xiangrui Meng <meng@databricks.com>
Closes#4680 from mengxr/SPARK-5897 and squashes the following commits:
847d216 [Xiangrui Meng] apache header
87719a2 [Xiangrui Meng] remove PIC image
2dd921f [Xiangrui Meng] update PIC user guide and add a Java example
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
Fixes SPARK-5805 : Fix the type error in the final example given in MLlib - Clustering documentation.
Author: Emre Sevinç <emre.sevinc@gmail.com>
Closes#4596 from emres/SPARK-5805 and squashes the following commits:
1029f66 [Emre Sevinç] SPARK-5805 Fixed the type error in documentation.
This is the LDA user guide from jkbradley with Java and Scala code example.
Author: Xiangrui Meng <meng@databricks.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#4465 from mengxr/lda-guide and squashes the following commits:
6dcb7d1 [Xiangrui Meng] update java example in the user guide
76169ff [Xiangrui Meng] update java example
36c3ae2 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into lda-guide
c2a1efe [Joseph K. Bradley] Added LDA programming guide, plus Java example (which is in the guide and probably should be removed).
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 single pseudo-eigenvector PIC
Including documentations and updated pom.xml with the following codes:
mllib/src/main/scala/org/apache/spark/mllib/clustering/PIClustering.scala
mllib/src/test/scala/org/apache/spark/mllib/clustering/PIClusteringSuite.scala
Author: sboeschhuawei <stephen.boesch@huawei.com>
Author: Fan Jiang <fanjiang.sc@huawei.com>
Author: Jiang Fan <fjiang6@gmail.com>
Author: Stephen Boesch <stephen.boesch@huawei.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#4254 from fjiang6/PIC and squashes the following commits:
4550850 [sboeschhuawei] Removed pic test data
f292f31 [Stephen Boesch] Merge pull request #44 from mengxr/SPARK-4259
4b78aaf [Xiangrui Meng] refactor PIC
24fbf52 [sboeschhuawei] Updated API to be similar to KMeans plus other changes requested by Xiangrui on the PR
c12dfc8 [sboeschhuawei] Removed examples files and added pic_data.txt. Revamped testcases yet to come
92d4752 [sboeschhuawei] Move the Guassian/ Affinity matrix calcs out of PIC. Presently in the test suite
7ebd149 [sboeschhuawei] Incorporate Xiangrui's first set of PR comments except restructure PIC.run to take Graph but do not remove Gaussian
121e4d5 [sboeschhuawei] Remove unused testing data files
1c3a62e [sboeschhuawei] removed matplot.py and reordered all private methods to bottom of PIC
218a49d [sboeschhuawei] Applied Xiangrui's comments - especially removing RDD/PICLinalg classes and making noncritical methods private
43ab10b [sboeschhuawei] Change last two println's to log4j logger
88aacc8 [sboeschhuawei] Add assert to testcase on cluster sizes
24f438e [sboeschhuawei] fixed incorrect markdown in clustering doc
060e6bf [sboeschhuawei] Added link to PIC doc from the main clustering md doc
be659e3 [sboeschhuawei] Added mllib specific log4j
90e7fa4 [sboeschhuawei] Converted from custom Linalg routines to Breeze: added JavaDoc comments; added Markdown documentation
bea48ea [sboeschhuawei] Converted custom Linear Algebra datatypes/routines to use Breeze.
b29c0db [Fan Jiang] Update PIClustering.scala
ace9749 [Fan Jiang] Update PIClustering.scala
a112f38 [sboeschhuawei] Added graphx main and test jars as dependencies to mllib/pom.xml
f656c34 [sboeschhuawei] Added iris dataset
b7dbcbe [sboeschhuawei] Added axes and combined into single plot for matplotlib
a2b1e57 [sboeschhuawei] Revert inadvertent update to KMeans
9294263 [sboeschhuawei] Added visualization/plotting of input/output data
e5df2b8 [sboeschhuawei] First end to end working PIC
0700335 [sboeschhuawei] First end to end working version: but has bad performance issue
32a90dc [sboeschhuawei] Update circles test data values
0ef163f [sboeschhuawei] Added ConcentricCircles data generation and KMeans clustering
3fd5bc8 [sboeschhuawei] PIClustering is running in new branch (up to the pseudo-eigenvector convergence step)
d5aae20 [Jiang Fan] Adding Power Iteration Clustering and Suite test
a3c5fbe [Jiang Fan] Adding Power Iteration Clustering
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
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.
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.
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
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.
(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/
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
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
