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* [SPARK-14891][ML] Add schema validation for ALSNick Pentreath2016-05-181-4/+4
| | | | | | | | | | | | | This PR adds schema validation to `ml`'s ALS and ALSModel. Currently, no schema validation was performed as `transformSchema` was never called in `ALS.fit` or `ALSModel.transform`. Furthermore, due to no schema validation, if users passed in Long (or Float etc) ids, they would be silently cast to Int with no warning or error thrown. With this PR, ALS now supports all numeric types for `user`, `item`, and `rating` columns. The rating column is cast to `Float` and the user and item cols are cast to `Int` (as is the case currently) - however for user/item, the cast throws an error if the value is outside integer range. Behavior for rating col is unchanged (as it is not an issue). ## How was this patch tested? New test cases in `ALSSuite`. Author: Nick Pentreath <nickp@za.ibm.com> Closes #12762 from MLnick/SPARK-14891-als-validate-schema.
* [SPARK-14978][PYSPARK] PySpark TrainValidationSplitModel should support ↵Takuya Kuwahara2016-05-182-10/+53
| | | | | | | | | | | | | | | | validationMetrics ## What changes were proposed in this pull request? This pull request includes supporting validationMetrics for TrainValidationSplitModel with Python and test for it. ## How was this patch tested? test in `python/pyspark/ml/tests.py` Author: Takuya Kuwahara <taakuu19@gmail.com> Closes #12767 from taku-k/spark-14978.
* [SPARK-14615][ML] Use the new ML Vector and Matrix in the ML pipeline based ↵DB Tsai2016-05-178-112/+94
| | | | | | | | | | | | | | | | | | algorithms ## What changes were proposed in this pull request? Once SPARK-14487 and SPARK-14549 are merged, we will migrate to use the new vector and matrix type in the new ml pipeline based apis. ## How was this patch tested? Unit tests Author: DB Tsai <dbt@netflix.com> Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Author: Xiangrui Meng <meng@databricks.com> Closes #12627 from dbtsai/SPARK-14615-NewML.
* [SPARK-14906][ML] Copy linalg in PySpark to new ML packageXiangrui Meng2016-05-172-45/+1556
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Copy the linalg (Vector/Matrix and VectorUDT/MatrixUDT) in PySpark to new ML package. ## How was this patch tested? Existing tests. Author: Xiangrui Meng <meng@databricks.com> Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #13099 from viirya/move-pyspark-vector-matrix-udt4.
* [SPARK-15181][ML][PYSPARK] Python API for GLR summaries.sethah2016-05-132-2/+238
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch adds a python API for generalized linear regression summaries (training and test). This helps provide feature parity for Python GLMs. ## How was this patch tested? Added a unit test to `pyspark.ml.tests` Author: sethah <seth.hendrickson16@gmail.com> Closes #12961 from sethah/GLR_summary.
* [MINOR][PYSPARK] update _shared_params_code_gen.pyZheng RuiFeng2016-05-133-10/+10
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? 1, add arg-checkings for `tol` and `stepSize` to keep in line with `SharedParamsCodeGen.scala` 2, fix one typo ## How was this patch tested? local build Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #12996 from zhengruifeng/py_args_checking.
* [SPARK-15188] Add missing thresholds param to NaiveBayes in PySparkHolden Karau2016-05-131-5/+10
| | | | | | | | | | | | | ## What changes were proposed in this pull request? Add missing thresholds param to NiaveBayes ## How was this patch tested? doctests Author: Holden Karau <holden@us.ibm.com> Closes #12963 from holdenk/SPARK-15188-add-missing-naive-bayes-param.
* [SPARK-15281][PYSPARK][ML][TRIVIAL] Add impurity param to GBTRegressor & add ↵Holden Karau2016-05-121-8/+44
| | | | | | | | | | | | | | | | experimental inside of regression.py ## What changes were proposed in this pull request? Add impurity param to GBTRegressor and mark the of the models & regressors in regression.py as experimental to match Scaladoc. ## How was this patch tested? Added default value to init, tested with unit/doc tests. Author: Holden Karau <holden@us.ibm.com> Closes #13071 from holdenk/SPARK-15281-GBTRegressor-impurity.
* [SPARK-15037] [SQL] [MLLIB] Part2: Use SparkSession instead of SQLContext in ↵Sandeep Singh2016-05-111-53/+44
| | | | | | | | | | | | | | Python TestSuites ## What changes were proposed in this pull request? Use SparkSession instead of SQLContext in Python TestSuites ## How was this patch tested? Existing tests Author: Sandeep Singh <sandeep@techaddict.me> Closes #13044 from techaddict/SPARK-15037-python.
* [SPARK-15189][PYSPARK][DOCS] Update ml.evaluation PyDocHolden Karau2016-05-111-1/+12
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fix doctest issue, short param description, and tag items as Experimental ## How was this patch tested? build docs locally & doctests Author: Holden Karau <holden@us.ibm.com> Closes #12964 from holdenk/SPARK-15189-ml.Evaluation-PyDoc-issues.
* [SPARK-15195][PYSPARK][DOCS] Update ml.tuning PyDocsHolden Karau2016-05-101-1/+15
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Tag classes in ml.tuning as experimental, add docs for kfolds avg metric, and copy TrainValidationSplit scaladoc for more detailed explanation. ## How was this patch tested? built docs locally Author: Holden Karau <holden@us.ibm.com> Closes #12967 from holdenk/SPARK-15195-pydoc-ml-tuning.
* [SPARK-15136][PYSPARK][DOC] Fix links to sphinx style and add a default ↵Holden Karau2016-05-094-22/+37
| | | | | | | | | | | | | | | | param doc note ## What changes were proposed in this pull request? PyDoc links in ml are in non-standard format. Switch to standard sphinx link format for better formatted documentation. Also add a note about default value in one place. Copy some extended docs from scala for GBT ## How was this patch tested? Built docs locally. Author: Holden Karau <holden@us.ibm.com> Closes #12918 from holdenk/SPARK-15137-linkify-pyspark-ml-classification.
* [SPARK-14050][ML] Add multiple languages support and additional methods for ↵Burak Köse2016-05-062-16/+29
| | | | | | | | | | | | | | | | | | | | | | | | | Stop Words Remover ## What changes were proposed in this pull request? This PR continues the work from #11871 with the following changes: * load English stopwords as default * covert stopwords to list in Python * update some tests and doc ## How was this patch tested? Unit tests. Closes #11871 cc: burakkose srowen Author: Burak Köse <burakks41@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Author: Burak KOSE <burakks41@gmail.com> Closes #12843 from mengxr/SPARK-14050.
* [SPARK-15106][PYSPARK][ML] Add PySpark package doc for ML component & remove ↵Holden Karau2016-05-051-0/+4
| | | | | | | | | | | | | | | | "BETA" ## What changes were proposed in this pull request? Copy the package documentation from Scala/Java to Python for ML package and remove beta tags. Not super sure if we want to keep the BETA tag but since we are making it the default it seems like probably the time to remove it (happy to put it back in if we want to keep it BETA). ## How was this patch tested? Python documentation built locally as HTML and text and verified output. Author: Holden Karau <holden@us.ibm.com> Closes #12883 from holdenk/SPARK-15106-add-pyspark-package-doc-for-ml.
* [SPARK-14971][ML][PYSPARK] PySpark ML Params setter code clean upYanbo Liang2016-05-0310-219/+110
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? PySpark ML Params setter code clean up. For examples, ```setInputCol``` can be simplified from ``` self._set(inputCol=value) return self ``` to: ``` return self._set(inputCol=value) ``` This is a pretty big sweeps, and we cleaned wherever possible. ## How was this patch tested? Exist unit tests. Author: Yanbo Liang <ybliang8@gmail.com> Closes #12749 from yanboliang/spark-14971.
* [SPARK-14931][ML][PYTHON] Mismatched default values between pipelines in ↵Xusen Yin2016-05-015-12/+62
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Spark and PySpark - update ## What changes were proposed in this pull request? This PR is an update for [https://github.com/apache/spark/pull/12738] which: * Adds a generic unit test for JavaParams wrappers in pyspark.ml for checking default Param values vs. the defaults in the Scala side * Various fixes for bugs found * This includes changing classes taking weightCol to treat unset and empty String Param values the same way. Defaults changed: * Scala * LogisticRegression: weightCol defaults to not set (instead of empty string) * StringIndexer: labels default to not set (instead of empty array) * GeneralizedLinearRegression: * maxIter always defaults to 25 (simpler than defaulting to 25 for a particular solver) * weightCol defaults to not set (instead of empty string) * LinearRegression: weightCol defaults to not set (instead of empty string) * Python * MultilayerPerceptron: layers default to not set (instead of [1,1]) * ChiSqSelector: numTopFeatures defaults to 50 (instead of not set) ## How was this patch tested? Generic unit test. Manually tested that unit test by changing defaults and verifying that broke the test. Author: Joseph K. Bradley <joseph@databricks.com> Author: yinxusen <yinxusen@gmail.com> Closes #12816 from jkbradley/yinxusen-SPARK-14931.
* [SPARK-14952][CORE][ML] Remove methods that were deprecated in 1.6.0Herman van Hovell2016-04-302-19/+0
| | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? This PR removes three methods the were deprecated in 1.6.0: - `PortableDataStream.close()` - `LinearRegression.weights` - `LogisticRegression.weights` The rationale for doing this is that the impact is small and that Spark 2.0 is a major release. #### How was this patch tested? Compilation succeded. Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #12732 from hvanhovell/SPARK-14952.
* [SPARK-13289][MLLIB] Fix infinite distances between word vectors in ↵Junyang2016-04-301-7/+8
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Word2VecModel ## What changes were proposed in this pull request? This PR fixes the bug that generates infinite distances between word vectors. For example, Before this PR, we have ``` val synonyms = model.findSynonyms("who", 40) ``` will give the following results: ``` to Infinity and Infinity that Infinity with Infinity ``` With this PR, the distance between words is a value between 0 and 1, as follows: ``` scala> model.findSynonyms("who", 10) res0: Array[(String, Double)] = Array((Harvard-educated,0.5253688097000122), (ex-SAS,0.5213794708251953), (McMutrie,0.5187736749649048), (fellow,0.5166833400726318), (businessman,0.5145374536514282), (American-born,0.5127736330032349), (British-born,0.5062344074249268), (gray-bearded,0.5047978162765503), (American-educated,0.5035858750343323), (mentored,0.49849334359169006)) scala> model.findSynonyms("king", 10) res1: Array[(String, Double)] = Array((queen,0.6787897944450378), (prince,0.6786158084869385), (monarch,0.659771203994751), (emperor,0.6490438580513), (goddess,0.643266499042511), (dynasty,0.635733425617218), (sultan,0.6166239380836487), (pharaoh,0.6150713562965393), (birthplace,0.6143025159835815), (empress,0.6109727025032043)) scala> model.findSynonyms("queen", 10) res2: Array[(String, Double)] = Array((princess,0.7670737504959106), (godmother,0.6982434988021851), (raven-haired,0.6877717971801758), (swan,0.684934139251709), (hunky,0.6816608309745789), (Titania,0.6808111071586609), (heroine,0.6794036030769348), (king,0.6787897944450378), (diva,0.67848801612854), (lip-synching,0.6731793284416199)) ``` ### There are two places changed in this PR: - Normalize the word vector to avoid overflow when calculating inner product between word vectors. This also simplifies the distance calculation, since the word vectors only need to be normalized once. - Scale the learning rate by number of iteration, to be consistent with Google Word2Vec implementation ## How was this patch tested? Use word2vec to train text corpus, and run model.findSynonyms() to get the distances between word vectors. Author: Junyang <fly.shenjy@gmail.com> Author: flyskyfly <fly.shenjy@gmail.com> Closes #11812 from flyjy/TVec.
* [SPARK-14412][.2][ML] rename *RDDStorageLevel to *StorageLevel in ml.ALSXiangrui Meng2016-04-302-40/+40
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? As discussed in #12660, this PR renames * intermediateRDDStorageLevel -> intermediateStorageLevel * finalRDDStorageLevel -> finalStorageLevel The argument name in `ALS.train` will be addressed in SPARK-15027. ## How was this patch tested? Existing unit tests. Author: Xiangrui Meng <meng@databricks.com> Closes #12803 from mengxr/SPARK-14412.
* [SPARK-14412][ML][PYSPARK] Add StorageLevel params to ALSNick Pentreath2016-04-292-5/+80
| | | | | | | | | | | | | | `mllib` `ALS` supports `setIntermediateRDDStorageLevel` and `setFinalRDDStorageLevel`. This PR adds these as Params in `ml` `ALS`. They are put in group **expertParam** since few users will need them. ## How was this patch tested? New test cases in `ALSSuite` and `tests.py`. cc yanboliang jkbradley sethah rishabhbhardwaj Author: Nick Pentreath <nickp@za.ibm.com> Closes #12660 from MLnick/SPARK-14412-als-storage-params.
* [SPARK-13786][ML][PYTHON] Removed save/load for python tuningJoseph K. Bradley2016-04-292-262/+21
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Per discussion on [https://github.com/apache/spark/pull/12604], this removes ML persistence for Python tuning (TrainValidationSplit, CrossValidator, and their Models) since they do not handle nesting easily. This support should be re-designed and added in the next release. ## How was this patch tested? Removed unit test elements saving and loading the tuning algorithms, but kept tests to save and load their bestModel fields. Author: Joseph K. Bradley <joseph@databricks.com> Closes #12782 from jkbradley/remove-python-tuning-saveload.
* [SPARK-11940][PYSPARK][ML] Python API for ml.clustering.LDA PR2Jeff Zhang2016-04-292-2/+543
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? pyspark.ml API for LDA * LDA, LDAModel, LocalLDAModel, DistributedLDAModel * includes persistence This replaces [https://github.com/apache/spark/pull/10242] ## How was this patch tested? * doc test for LDA, including Param setters * unit test for persistence Author: Joseph K. Bradley <joseph@databricks.com> Author: Jeff Zhang <zjffdu@apache.org> Closes #12723 from jkbradley/zjffdu-SPARK-11940.
* [SPARK-12810][PYSPARK] PySpark CrossValidatorModel should support avgMetricsKai Jiang2016-04-282-8/+37
| | | | | | | | | | | | ## What changes were proposed in this pull request? support avgMetrics in CrossValidatorModel with Python ## How was this patch tested? Doctest and `test_save_load` in `pyspark/ml/test.py` [JIRA](https://issues.apache.org/jira/browse/SPARK-12810) Author: Kai Jiang <jiangkai@gmail.com> Closes #12464 from vectorijk/spark-12810.
* [SPARK-14899][ML][PYSPARK] Remove spark.ml HashingTF hashingAlg optionYanbo Liang2016-04-272-36/+14
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Since [SPARK-10574](https://issues.apache.org/jira/browse/SPARK-10574) breaks behavior of ```HashingTF```, we should try to enforce good practice by removing the "native" hashAlgorithm option in spark.ml and pyspark.ml. We can leave spark.mllib and pyspark.mllib alone. ## How was this patch tested? Unit tests. cc jkbradley Author: Yanbo Liang <ybliang8@gmail.com> Closes #12702 from yanboliang/spark-14899.
* [SPARK-14732][ML] spark.ml GaussianMixture should use MultivariateGaussian ↵Joseph K. Bradley2016-04-261-7/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | in mllib-local ## What changes were proposed in this pull request? Before, spark.ml GaussianMixtureModel used the spark.mllib MultivariateGaussian in its public API. This was added after 1.6, so we can modify this API without breaking APIs. This PR copies MultivariateGaussian to mllib-local in spark.ml, with a few changes: * Renamed fields to match numpy, scipy: mu => mean, sigma => cov This PR then uses the spark.ml MultivariateGaussian in the spark.ml GaussianMixtureModel, which involves: * Modifying the constructor * Adding a computeProbabilities method Also: * Added EPSILON to mllib-local for use in MultivariateGaussian ## How was this patch tested? Existing unit tests Author: Joseph K. Bradley <joseph@databricks.com> Closes #12593 from jkbradley/sparkml-gmm-fix.
* [SPARK-14903][SPARK-14071][ML][PYTHON] Revert : MLWritable.write propertyJoseph K. Bradley2016-04-262-8/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? SPARK-14071 changed MLWritable.write to be a property. This reverts that change since there was not a good way to make MLReadable.read appear to be a property. ## How was this patch tested? existing unit tests Author: Joseph K. Bradley <joseph@databricks.com> Closes #12671 from jkbradley/revert-MLWritable-write-py.
* [SPARK-11559][MLLIB] Make `runs` no effect in mllib.KMeansYanbo Liang2016-04-261-3/+2
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? We deprecated ```runs``` of mllib.KMeans in Spark 1.6 (SPARK-11358). In 2.0, we will make it no effect (with warning messages). We did not remove ```setRuns/getRuns``` for better binary compatibility. This PR change `runs` which are appeared at the public API. Usage inside of ```KMeans.runAlgorithm()``` will be resolved at #10806. ## How was this patch tested? Existing unit tests. cc jkbradley Author: Yanbo Liang <ybliang8@gmail.com> Closes #12608 from yanboliang/spark-11559.
* [SPARK-10574][ML][MLLIB] HashingTF supports MurmurHash3Yanbo Liang2016-04-252-9/+33
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? As the discussion at [SPARK-10574](https://issues.apache.org/jira/browse/SPARK-10574), ```HashingTF``` should support MurmurHash3 and make it as the default hash algorithm. We should also expose set/get API for ```hashAlgorithm```, then users can choose the hash method. Note: The problem that ```mllib.feature.HashingTF``` behaves differently between Scala/Java and Python will be resolved in the followup work. ## How was this patch tested? unit tests. cc jkbradley MLnick Author: Yanbo Liang <ybliang8@gmail.com> Author: Joseph K. Bradley <joseph@databricks.com> Closes #12498 from yanboliang/spark-10574.
* [MINOR][ML][PYTHON][DOC] Remove use of JavaMLWriter/Reader in public Python ↵Joseph K. Bradley2016-04-251-4/+4
| | | | | | | | | | | | | | | | API docs ## What changes were proposed in this pull request? Removed instances of JavaMLWriter, JavaMLReader appearing in public Python API docs ## How was this patch tested? n/a Author: Joseph K. Bradley <joseph@databricks.com> Closes #12542 from jkbradley/javamlwriter-doc.
* [SPARK-14433][PYSPARK][ML] PySpark ml GaussianMixturewm624@hotmail.com2016-04-251-1/+145
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add Python API in ML for GaussianMixture ## How was this patch tested? (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) Add doctest and test cases are the same as mllib Python tests ./dev/lint-python PEP8 checks passed. rm -rf _build/* pydoc checks passed. ./python/run-tests --python-executables=python2.7 --modules=pyspark-ml Running PySpark tests. Output is in /Users/mwang/spark_ws_0904/python/unit-tests.log Will test against the following Python executables: ['python2.7'] Will test the following Python modules: ['pyspark-ml'] Finished test(python2.7): pyspark.ml.evaluation (18s) Finished test(python2.7): pyspark.ml.clustering (40s) Finished test(python2.7): pyspark.ml.classification (49s) Finished test(python2.7): pyspark.ml.recommendation (44s) Finished test(python2.7): pyspark.ml.feature (64s) Finished test(python2.7): pyspark.ml.regression (45s) Finished test(python2.7): pyspark.ml.tuning (30s) Finished test(python2.7): pyspark.ml.tests (56s) Tests passed in 106 seconds Author: wm624@hotmail.com <wm624@hotmail.com> Closes #12402 from wangmiao1981/gmm.
* [SPARK-14768][ML][PYSPARK] removed expectedType from Param __init__()Jason Lee2016-04-251-8/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? Removed expectedType arg from PySpark Param __init__, as suggested by the JIRA. ## How was this patch tested? Manually looked through all places that use Param. Compiled and ran all ML PySpark test cases before and after the fix. Author: Jason Lee <cjlee@us.ibm.com> Closes #12581 from jasoncl/SPARK-14768.
* [MINOR][ML][PYSPARK] Fix omissive params which should use TypeConverterYanbo Liang2016-04-202-4/+5
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? #11663 adds type conversion functionality for parameters in Pyspark. This PR find out the omissive ```Param``` that did not pass corresponding ```TypeConverter``` argument and fix them. After this PR, all params in pyspark/ml/ used ```TypeConverter```. ## How was this patch tested? Existing tests. cc jkbradley sethah Author: Yanbo Liang <ybliang8@gmail.com> Closes #12529 from yanboliang/typeConverter.
* [MINOR][ML][PYSPARK] Fix omissive param setters which should use _set methodYanbo Liang2016-04-201-2/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? #11939 make Python param setters use the `_set` method. This PR fix omissive ones. ## How was this patch tested? Existing tests. cc jkbradley sethah Author: Yanbo Liang <ybliang8@gmail.com> Closes #12531 from yanboliang/setters-omissive.
* [SPARK-14555] First cut of Python API for Structured StreamingBurak Yavuz2016-04-2010-28/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes: - ContinuousQuery - Trigger - ProcessingTime in pyspark under `pyspark.sql.streaming`. In addition, it contains the new methods added under: - `DataFrameWriter` a) `startStream` b) `trigger` c) `queryName` - `DataFrameReader` a) `stream` - `DataFrame` a) `isStreaming` This PR doesn't contain all methods exposed for `ContinuousQuery`, for example: - `exception` - `sourceStatuses` - `sinkStatus` They may be added in a follow up. This PR also contains some very minor doc fixes in the Scala side. ## How was this patch tested? Python doc tests TODO: - [ ] verify Python docs look good Author: Burak Yavuz <brkyvz@gmail.com> Author: Burak Yavuz <burak@databricks.com> Closes #12320 from brkyvz/stream-python.
* [SPARK-14714][ML][PYTHON] Fixed issues with non-kwarg typeConverter arg for ↵Joseph K. Bradley2016-04-183-13/+19
| | | | | | | | | | | | | | | | | | | | | | | | | Param constructor ## What changes were proposed in this pull request? PySpark Param constructors need to pass the TypeConverter argument by name, partly to make sure it is not mistaken for the expectedType arg and partly because we will remove the expectedType arg in 2.1. In several places, this is not being done correctly. This PR changes all usages in pyspark/ml/ to keyword args. ## How was this patch tested? Existing unit tests. I will not test type conversion for every Param unless we really think it necessary. Also, if you start the PySpark shell and import classes (e.g., pyspark.ml.feature.StandardScaler), then you no longer get this warning: ``` /Users/josephkb/spark/python/pyspark/ml/param/__init__.py:58: UserWarning: expectedType is deprecated and will be removed in 2.1. Use typeConverter instead, as a keyword argument. "Use typeConverter instead, as a keyword argument.") ``` That warning came from the typeConverter argument being passes as the expectedType arg by mistake. Author: Joseph K. Bradley <joseph@databricks.com> Closes #12480 from jkbradley/typeconverter-fix.
* [SPARK-14440][PYSPARK] Remove pipeline specific reader and writerXusen Yin2016-04-181-46/+7
| | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-14440 Remove * PipelineMLWriter * PipelineMLReader * PipelineModelMLWriter * PipelineModelMLReader and modify comments. ## How was this patch tested? test with unit test. Author: Xusen Yin <yinxusen@gmail.com> Closes #12216 from yinxusen/SPARK-14440.
* [SPARK-14564][ML][MLLIB][PYSPARK] Python Word2Vec missing setWindowSize methodJason Lee2016-04-182-5/+28
| | | | | | | | | | | | ## What changes were proposed in this pull request? Added windowSize getter/setter to ML/MLlib ## How was this patch tested? Added test cases in tests.py under both ML and MLlib Author: Jason Lee <cjlee@us.ibm.com> Closes #12428 from jasoncl/SPARK-14564.
* [SPARK-14306][ML][PYSPARK] PySpark ml.classification OneVsRest support ↵Xusen Yin2016-04-182-23/+144
| | | | | | | | | | | | | | | | | | export/import ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-14306 Add PySpark OneVsRest save/load supports. ## How was this patch tested? Test with Python unit test. Author: Xusen Yin <yinxusen@gmail.com> Closes #12439 from yinxusen/SPARK-14306-0415.
* [SPARK-14605][ML][PYTHON] Changed Python to use unicode UIDs for spark.ml ↵Joseph K. Bradley2016-04-164-4/+8
| | | | | | | | | | | | | | | | | | Identifiable ## What changes were proposed in this pull request? Python spark.ml Identifiable classes use UIDs of type str, but they should use unicode (in Python 2.x) to match Java. This could be a problem if someone created a class in Java with odd unicode characters, saved it, and loaded it in Python. This PR: Use unicode everywhere in Python. ## How was this patch tested? Updated persistence unit test to check uid type Author: Joseph K. Bradley <joseph@databricks.com> Closes #12368 from jkbradley/python-uid-unicode.
* [SPARK-7861][ML] PySpark OneVsRestXusen Yin2016-04-152-7/+249
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-7861 Add PySpark OneVsRest. I implement it with Python since it's a meta-pipeline. ## How was this patch tested? Test with doctest. Author: Xusen Yin <yinxusen@gmail.com> Closes #12124 from yinxusen/SPARK-14306-7861.
* [SPARK-14104][PYSPARK][ML] All Python param setters should use the `_set` methodsethah2016-04-1512-91/+110
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Param setters in python previously accessed the _paramMap directly to update values. The `_set` method now implements type checking, so it should be used to update all parameters. This PR eliminates all direct accesses to `_paramMap` besides the one in the `_set` method to ensure type checking happens. Additional changes: * [SPARK-13068](https://github.com/apache/spark/pull/11663) missed adding type converters in evaluation.py so those are done here * An incorrect `toBoolean` type converter was used for StringIndexer `handleInvalid` param in previous PR. This is fixed here. ## How was this patch tested? Existing unit tests verify that parameters are still set properly. No new functionality is actually added in this PR. Author: sethah <seth.hendrickson16@gmail.com> Closes #11939 from sethah/SPARK-14104.
* [SPARK-14665][ML][PYTHON] Fixed bug with StopWordsRemover default stopwordsJoseph K. Bradley2016-04-152-1/+4
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The default stopwords were a Java object. They are no longer. ## How was this patch tested? Unit test which failed before the fix Author: Joseph K. Bradley <joseph@databricks.com> Closes #12422 from jkbradley/pyspark-stopwords.
* [SPARK-14374][ML][PYSPARK] PySpark ml GBTClassifier, Regressor support ↵Yanbo Liang2016-04-142-4/+30
| | | | | | | | | | | | | | | | export/import ## What changes were proposed in this pull request? PySpark ml GBTClassifier, Regressor support export/import. ## How was this patch tested? Doc test. cc jkbradley Author: Yanbo Liang <ybliang8@gmail.com> Closes #12383 from yanboliang/spark-14374.
* [SPARK-14238][ML][MLLIB][PYSPARK] Add binary toggle Param to PySpark ↵Yong Tang2016-04-142-2/+41
| | | | | | | | | | | | | | | | | | HashingTF in ML & MLlib ## What changes were proposed in this pull request? This fix tries to add binary toggle Param to PySpark HashingTF in ML & MLlib. If this toggle is set, then all non-zero counts will be set to 1. Note: This fix (SPARK-14238) is extended from SPARK-13963 where Scala implementation was done. ## How was this patch tested? This fix adds two tests to cover the code changes. One for HashingTF in PySpark's ML and one for HashingTF in PySpark's MLLib. Author: Yong Tang <yong.tang.github@outlook.com> Closes #12079 from yongtang/SPARK-14238.
* [SPARK-13967][PYSPARK][ML] Added binary Param to Python CountVectorizerBryan Cutler2016-04-142-5/+45
| | | | | | | | | | Added binary toggle param to CountVectorizer feature transformer in PySpark. Created a unit test for using CountVectorizer with the binary toggle on. Author: Bryan Cutler <cutlerb@gmail.com> Closes #12308 from BryanCutler/binary-param-python-CountVectorizer-SPARK-13967.
* [SPARK-14573][PYSPARK][BUILD] Fix PyDoc Makefile & highlighting issuesHolden Karau2016-04-141-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The PyDoc Makefile used "=" rather than "?=" for setting env variables so it overwrote the user values. This ignored the environment variables we set for linting allowing warnings through. This PR also fixes the warnings that had been introduced. ## How was this patch tested? manual local export & make Author: Holden Karau <holden@us.ibm.com> Closes #12336 from holdenk/SPARK-14573-fix-pydoc-makefile.
* [SPARK-14472][PYSPARK][ML] Cleanup ML JavaWrapper and related class hierarchyBryan Cutler2016-04-138-70/+62
| | | | | | | | | | Currently, JavaWrapper is only a wrapper class for pipeline classes that have Params and JavaCallable is a separate mixin that provides methods to make Java calls. This change simplifies the class structure and to define the Java wrapper in a plain base class along with methods to make Java calls. Also, renames Java wrapper classes to better reflect their purpose. Ran existing Python ml tests and generated documentation to test this change. Author: Bryan Cutler <cutlerb@gmail.com> Closes #12304 from BryanCutler/pyspark-cleanup-JavaWrapper-SPARK-14472.
* [SPARK-13597][PYSPARK][ML] Python API for GeneralizedLinearRegressionKai Jiang2016-04-121-0/+145
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Python API for GeneralizedLinearRegression JIRA: https://issues.apache.org/jira/browse/SPARK-13597 ## How was this patch tested? The patch is tested with Python doctest. Author: Kai Jiang <jiangkai@gmail.com> Closes #11468 from vectorijk/spark-13597.
* [SPARK-14498][ML][PYTHON][SQL] Many cleanups to ML and ML-related docsJoseph K. Bradley2016-04-084-2/+13
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Cleanups to documentation. No changes to code. * GBT docs: Move Scala doc for private object GradientBoostedTrees to public docs for GBTClassifier,Regressor * GLM regParam: needs doc saying it is for L2 only * TrainValidationSplitModel: add .. versionadded:: 2.0.0 * Rename “_transformer_params_from_java” to “_transfer_params_from_java” * LogReg Summary classes: “probability” col should not say “calibrated” * LR summaries: coefficientStandardErrors —> document that intercept stderr comes last. Same for t,p-values * approxCountDistinct: Document meaning of “rsd" argument. * LDA: note which params are for online LDA only ## How was this patch tested? Doc build Author: Joseph K. Bradley <joseph@databricks.com> Closes #12266 from jkbradley/ml-doc-cleanups.
* [SPARK-12569][PYSPARK][ML] DecisionTreeRegressor: provide variance of ↵wm624@hotmail.com2016-04-083-7/+35
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | prediction: Python API ## What changes were proposed in this pull request? A new column VarianceCol has been added to DecisionTreeRegressor in ML scala code. This patch adds the corresponding Python API, HasVarianceCol, to class DecisionTreeRegressor. ## How was this patch tested? ./dev/lint-python PEP8 checks passed. rm -rf _build/* pydoc checks passed. ./python/run-tests --python-executables=python2.7 --modules=pyspark-ml Running PySpark tests. Output is in /Users/mwang/spark_ws_0904/python/unit-tests.log Will test against the following Python executables: ['python2.7'] Will test the following Python modules: ['pyspark-ml'] Finished test(python2.7): pyspark.ml.evaluation (12s) Finished test(python2.7): pyspark.ml.clustering (18s) Finished test(python2.7): pyspark.ml.classification (30s) Finished test(python2.7): pyspark.ml.recommendation (28s) Finished test(python2.7): pyspark.ml.feature (43s) Finished test(python2.7): pyspark.ml.regression (31s) Finished test(python2.7): pyspark.ml.tuning (19s) Finished test(python2.7): pyspark.ml.tests (34s) (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: wm624@hotmail.com <wm624@hotmail.com> Closes #12116 from wangmiao1981/fix_api.
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