Author: Kashif Rasul <kashif.rasul@gmail.com>
Closes#7269 from kashif/SPARK-8872 and squashes the following commits:
2d5457f [Kashif Rasul] added R code for FP Int type
3de6808 [Kashif Rasul] added verification results from R for FPGrowthSuite
In LinearRegression and LogisticRegression, we use Breeze's optimizers (LBFGS and OWLQN). We check the State.value to see the current objective. However, Breeze's documentation makes it sound like value and adjustedValue differ for some optimizers, possibly including OWLQN: 26faf62286/math/src/main/scala/breeze/optimize/FirstOrderMinimizer.scala (L36)
If that is the case, then we should use adjustedValue instead of value. This is relevant to SPARK-8538 and SPARK-8539, where we will provide the objective trace to the user.
Author: DB Tsai <dbt@netflix.com>
Closes#7245 from dbtsai/SPARK-8845 and squashes the following commits:
fa4c91e [DB Tsai] address feedback
e6caac1 [DB Tsai] java style multiline comment
b10c574 [DB Tsai] address feedback
c9ff81e [DB Tsai] first commit
Add std, mean to StandardScalerModel
getVectors, findSynonyms to Word2Vec Model
setFeatures and getFeatures to hashingTF
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#7086 from MechCoder/missing_model_methods and squashes the following commits:
9fbae90 [MechCoder] Add type
6e3d6b2 [MechCoder] [SPARK-8704] Add missing methods in StandardScaler (ML and PySpark)
Distributed generation of single-consequent association rules from a RDD of frequent itemsets. Tests referenced against `R`'s implementation of A Priori in [arules](http://cran.r-project.org/web/packages/arules/index.html).
Author: Feynman Liang <fliang@databricks.com>
Closes#7005 from feynmanliang/fp-association-rules-distributed and squashes the following commits:
466ced0 [Feynman Liang] Refactor AR generation impl
73c1cff [Feynman Liang] Make rule attributes public, remove numTransactions from FreqItemset
80f63ff [Feynman Liang] Change default confidence and optimize imports
04cf5b5 [Feynman Liang] Code review with @mengxr, add R to tests
0cc1a6a [Feynman Liang] Java compatibility test
f3c14b5 [Feynman Liang] Fix MiMa test
764375e [Feynman Liang] Fix tests
1187307 [Feynman Liang] Almost working tests
b20779b [Feynman Liang] Working implementation
5395c4e [Feynman Liang] Fix imports
2d34405 [Feynman Liang] Partial implementation of distributed ar
83ace4b [Feynman Liang] Local rule generation without pruning complete
69c2c87 [Feynman Liang] Working local implementation, now to parallelize../..
4e1ec9a [Feynman Liang] Pull FreqItemsets out, refactor type param, tests
69ccedc [Feynman Liang] First implementation of association rule generation
Add numNodes and depth to treeModels, add treeWeights to ensemble Models.
Add __repr__ to all models.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#7095 from MechCoder/missing_methods_tree and squashes the following commits:
23b08be [MechCoder] private [spark]
38a0860 [MechCoder] rename pyTreeWeights to javaTreeWeights
6d16ad8 [MechCoder] Fix Python 3 Error
47d7023 [MechCoder] Use np.allclose and treeEnsembleModel -> TreeEnsembleMethods
819098c [MechCoder] [SPARK-8711] [ML] Add additional methods ot PySpark ML tree models
Add Java unit test for PCA transformer
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7184 from yanboliang/spark-8788 and squashes the following commits:
9d1a2af [Yanbo Liang] address comments
b34451f [Yanbo Liang] Add Java unit test for PCA transformer
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.
This reverts commit 25f574eb9a. After speaking to some users and developers, we realized that FP-growth doesn't meet the requirement for frequent sequence mining. PrefixSpan (SPARK-6487) would be the correct algorithm for it. feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#7240 from mengxr/SPARK-7212.revert and squashes the following commits:
2b3d66b [Xiangrui Meng] Revert "[SPARK-7212] [MLLIB] Add sequence learning flag"
Author: Joshi <rekhajoshm@gmail.com>
Author: Rekha Joshi <rekhajoshm@gmail.com>
Closes#5992 from rekhajoshm/fix/SPARK-7137 and squashes the following commits:
8c42b57 [Joshi] update checkInputColumn to print more info if needed
33ddd2e [Joshi] update checkInputColumn to print more info if needed
acf3e17 [Joshi] update checkInputColumn to print more info if needed
8993c0e [Joshi] SPARK-7137: Add checkInputColumn back to Params and print more info
e3677c9 [Rekha Joshi] Merge pull request #1 from apache/master
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#6821 from yu-iskw/SPARK-7104 and squashes the following commits:
975136b [Yu ISHIKAWA] Organize import
0ef58b6 [Yu ISHIKAWA] Use rmtree, instead of removedirs
cb21653 [Yu ISHIKAWA] Add an explicit type for `Word2VecModelWrapper.save`
1d468ef [Yu ISHIKAWA] [SPARK-7104][MLlib] Support model save/load in Python's Word2Vec
GrandientDescent can receive convergence tolerance value. Default value is 0.0.
When loss value becomes less than the tolerance which is set by user, iteration is terminated.
Author: lewuathe <lewuathe@me.com>
Closes#3636 from Lewuathe/gd-convergence-tolerance and squashes the following commits:
0b8a9a8 [lewuathe] Update doc
ce91b15 [lewuathe] Merge branch 'master' into gd-convergence-tolerance
4f22c2b [lewuathe] Modify based on SPARK-1503
5e47b82 [lewuathe] Merge branch 'master' into gd-convergence-tolerance
abadb7e [lewuathe] Fix LassoSuite
8fadebd [lewuathe] Fix failed unit tests
ee5de46 [lewuathe] Merge branch 'master' into gd-convergence-tolerance
8313ba2 [lewuathe] Fix styles
0ead94c [lewuathe] Merge branch 'master' into gd-convergence-tolerance
a94cfd5 [lewuathe] Modify some styles
3aef0a2 [lewuathe] Modify converged logic to do relative comparison
f7b19d5 [lewuathe] [SPARK-3382] Clarify comparison logic
e6c9cd2 [lewuathe] [SPARK-3382] Compare with the diff of solution vector
4b125d2 [lewuathe] [SPARK3382] Fix scala style
e7c10dd [lewuathe] [SPARK-3382] format improvements
f867eea [lewuathe] [SPARK-3382] Modify warning message statements
b9d5e61 [lewuathe] [SPARK-3382] should compare diff inside loss history and convergence tolerance
5433f71 [lewuathe] [SPARK-3382] GradientDescent convergence tolerance
Matrices allow zeros to be stored in values. Sometimes a method is handy to check if the numNonZeros are same as number of Active values.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6904 from MechCoder/nnz_matrix and squashes the following commits:
252c6b7 [MechCoder] Add to MiMa excludes
e2390f5 [MechCoder] Use count instead of foreach
2f62b2f [MechCoder] Add to MiMa excludes
d6e96ef [MechCoder] [SPARK-8479] Add numNonzeros and numActives to linalg.Matrices
JIRA: https://issues.apache.org/jira/browse/SPARK-8708
Previously the partitions of ratings are only based on the given products. So if the `usersProducts` given for prediction contains only few products or even one product, the generated ratings will be pushed into few or single partition and can't use high parallelism.
The following codes are the example reported in the JIRA. Because it asks the predictions for users on product 2. There is only one partition in the result.
>>> r1 = (1, 1, 1.0)
>>> r2 = (1, 2, 2.0)
>>> r3 = (2, 1, 2.0)
>>> r4 = (2, 2, 2.0)
>>> r5 = (3, 1, 1.0)
>>> ratings = sc.parallelize([r1, r2, r3, r4, r5], 5)
>>> users = ratings.map(itemgetter(0)).distinct()
>>> model = ALS.trainImplicit(ratings, 1, seed=10)
>>> predictions_for_2 = model.predictAll(users.map(lambda u: (u, 2)))
>>> predictions_for_2.glom().map(len).collect()
[0, 0, 3, 0, 0]
This PR uses user and product instead of only product to partition the ratings.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7121 from viirya/mfm_fix_partition and squashes the following commits:
779946d [Liang-Chi Hsieh] Calculate approximate numbers of users and products in one pass.
4336dc2 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into mfm_fix_partition
83e56c1 [Liang-Chi Hsieh] Instead of additional join, use the numbers of users and products to decide how to perform join.
b534dc8 [Liang-Chi Hsieh] Paritition ratings based on both users and products.
I added the code,
// see [SPARK-8647], this achieves the needed constant hash code without constant no.
override def hashCode(): Int = this.getClass.getName.hashCode()
does getting the constant hash code as per jira
Author: Alok Singh <singhal@Aloks-MacBook-Pro.local>
Closes#7146 from aloknsingh/aloknsingh_SPARK-8647 and squashes the following commits:
e58bccf [Alok Singh] [SPARK-8647][MLlib] to avoid the class derivation issues, change the constant hashCode to override def hashCode(): Int = classOf[MatrixUDT].getName.hashCode()
43cdb89 [Alok Singh] [SPARK-8647][MLlib] Potential issue with constant hashCode
I've updated default values in comments, documentation, and in the command line builder to be 1g based on comments in the JIRA. I've also updated most usages to point at a single variable defined in the Utils.scala and JavaUtils.java files. This wasn't possible in all cases (R, shell scripts etc.) but usage in most code is now pointing at the same place.
Please let me know if I've missed anything.
Will the spark-shell use the value within the command line builder during instantiation?
Author: Ilya Ganelin <ilya.ganelin@capitalone.com>
Closes#7132 from ilganeli/SPARK-3071 and squashes the following commits:
4074164 [Ilya Ganelin] String fix
271610b [Ilya Ganelin] Merge branch 'SPARK-3071' of github.com:ilganeli/spark into SPARK-3071
273b6e9 [Ilya Ganelin] Test fix
fd67721 [Ilya Ganelin] Update JavaUtils.java
26cc177 [Ilya Ganelin] test fix
e5db35d [Ilya Ganelin] Fixed test failure
39732a1 [Ilya Ganelin] merge fix
a6f7deb [Ilya Ganelin] Created default value for DRIVER MEM in Utils that's now used in almost all locations instead of setting manually in each
09ad698 [Ilya Ganelin] Update SubmitRestProtocolSuite.scala
19b6f25 [Ilya Ganelin] Missed one doc update
2698a3d [Ilya Ganelin] Updated default value for driver memory
'>' symbols removed from comments in LogisticRegressionSuite.scala, for ease of copypaste
also single-lined the multiline commands (is this desirable, or does it violate style?)
Author: Rosstin <asterazul@gmail.com>
Closes#7167 from Rosstin/SPARK-8660-2 and squashes the following commits:
f4b9bc8 [Rosstin] SPARK-8660 restored character limit on multiline comments in LogisticRegressionSuite.scala
fe6b112 [Rosstin] SPARK-8660 > symbols removed from LogisticRegressionSuite.scala for easy of copypaste
39ddd50 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8661
5a05dee [Rosstin] SPARK-8661 for LinearRegressionSuite.scala, changed javadoc-style comments to regular multiline comments to make it easier to copy-paste the R code.
bb9a4b1 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8660
242aedd [Rosstin] SPARK-8660, changed comment style from JavaDoc style to normal multiline comment in order to make copypaste into R easier, in file classification/LogisticRegressionSuite.scala
2cd2985 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8639
21ac1e5 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8639
6c18058 [Rosstin] fixed minor typos in docs/README.md and docs/api.md
Rename DiscreteCosineTransformer and related classes to DCT.
Author: Feynman Liang <fliang@databricks.com>
Closes#7138 from feynmanliang/dct-features and squashes the following commits:
e547b3e [Feynman Liang] Fix renaming bug
9d5c9e4 [Feynman Liang] Lowercase JavaDCTSuite variable
f9a8958 [Feynman Liang] Remove old files
f8fe794 [Feynman Liang] Merge branch 'master' into dct-features
894d0b2 [Feynman Liang] Rename DiscreteCosineTransformer to DCT
433dbc7 [Feynman Liang] Test refactoring
91e9636 [Feynman Liang] Style guide and test helper refactor
b5ac19c [Feynman Liang] Use Vector types, add Java test
530983a [Feynman Liang] Tests for other numeric datatypes
195d7aa [Feynman Liang] Implement support for arbitrary numeric types
95d4939 [Feynman Liang] Working DCT for 1D Doubles
I'm sorry that I made https://github.com/apache/spark/pull/6949 closed by mistake.
I pushed codes again.
And, I added a test code.
>
There is a bug that `U.numCols() = self.nCols` in `IndexedRowMatrix.computeSVD()`
It should have been `U.numCols() = k = svd.U.numCols()`
>
```
self = U * sigma * V.transpose
(m x n) = (m x n) * (k x k) * (k x n) //ASIS
-->
(m x n) = (m x k) * (k x k) * (k x n) //TOBE
```
Author: lee19 <lee19@live.co.kr>
Closes#6953 from lee19/MLlibBugfix and squashes the following commits:
c1812a0 [lee19] [SPARK-8563] [MLlib] Used nRows instead of numRows() to reduce a burden.
4b9803b [lee19] [SPARK-8563] [MLlib] Fixed a build error.
c2ccd89 [lee19] Added a unit test that validates matrix sizes of svd for [SPARK-8563][MLlib]
8373424 [lee19] [SPARK-8563][MLlib] Fixed a bug so that IndexedRowMatrix.computeSVD().U.numCols = k
Changed GBTRegressor so it does NOT threshold the prediction. Added test which fails with bug but works after fix.
CC: feynmanliang mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#7134 from jkbradley/gbrt-fix and squashes the following commits:
613b90e [Joseph K. Bradley] Changed GBTRegressor so it does NOT threshold the prediction
jira: https://issues.apache.org/jira/browse/SPARK-7514
Add a popular scaling method to feature component, which is commonly known as min-max normalization or Rescaling.
Core function is,
Normalized(x) = (x - min) / (max - min) * scale + newBase
where `newBase` and `scale` are parameters (type Double) of the `VectorTransformer`. `newBase` is the new minimum number for the features, and `scale` controls the ranges after transformation. This is a little complicated than the basic MinMax normalization, yet it provides flexibility so that users can control the range more specifically. like [0.1, 0.9] in some NN application.
For case that `max == min`, 0.5 is used as the raw value. (0.5 * scale + newBase)
I'll add UT once the design got settled ( and this is not considered as too naive)
reference:
http://en.wikipedia.org/wiki/Feature_scalinghttp://stn.spotfire.com/spotfire_client_help/index.htm#norm/norm_scale_between_0_and_1.htm
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6039 from hhbyyh/minMaxNorm and squashes the following commits:
f942e9f [Yuhao Yang] add todo for metadata
8b37bbc [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
4894dbc [Yuhao Yang] add copy
fa2989f [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
29db415 [Yuhao Yang] add clue and minor adjustment
5b8f7cc [Yuhao Yang] style fix
9b133d0 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
22f20f2 [Yuhao Yang] style change and bug fix
747c9bb [Yuhao Yang] add ut and remove mllib version
a5ba0aa [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
585cc07 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
1c6dcb1 [Yuhao Yang] minor change
0f1bc80 [Yuhao Yang] add MinMaxScaler to ml
8e7436e [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
3663165 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into minMaxNorm
1247c27 [Yuhao Yang] some comments improvement
d285a19 [Yuhao Yang] initial checkin for minMaxNorm
Implementation and tests for Discrete Cosine Transformer.
Author: Feynman Liang <fliang@databricks.com>
Closes#6894 from feynmanliang/dct-features and squashes the following commits:
433dbc7 [Feynman Liang] Test refactoring
91e9636 [Feynman Liang] Style guide and test helper refactor
b5ac19c [Feynman Liang] Use Vector types, add Java test
530983a [Feynman Liang] Tests for other numeric datatypes
195d7aa [Feynman Liang] Implement support for arbitrary numeric types
95d4939 [Feynman Liang] Working DCT for 1D Doubles
Add PCA transformer for ML pipeline
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7065 from yanboliang/spark-8664 and squashes the following commits:
4afae45 [Yanbo Liang] address comments
e9effd7 [Yanbo Liang] Add PCA transformer
for mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala, changed javadoc-style comments to regular multiline comments, to make copy-pasting R code more simple
Author: Rosstin <asterazul@gmail.com>
Closes#7098 from Rosstin/SPARK-8661 and squashes the following commits:
5a05dee [Rosstin] SPARK-8661 for LinearRegressionSuite.scala, changed javadoc-style comments to regular multiline comments to make it easier to copy-paste the R code.
bb9a4b1 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8660
242aedd [Rosstin] SPARK-8660, changed comment style from JavaDoc style to normal multiline comment in order to make copypaste into R easier, in file classification/LogisticRegressionSuite.scala
2cd2985 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8639
21ac1e5 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8639
6c18058 [Rosstin] fixed minor typos in docs/README.md and docs/api.md
Converted JavaDoc style comments in mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala to regular multiline comments, to make copy-pasting R commands easier.
Author: Rosstin <asterazul@gmail.com>
Closes#7096 from Rosstin/SPARK-8660 and squashes the following commits:
242aedd [Rosstin] SPARK-8660, changed comment style from JavaDoc style to normal multiline comment in order to make copypaste into R easier, in file classification/LogisticRegressionSuite.scala
2cd2985 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8639
21ac1e5 [Rosstin] Merge branch 'master' of github.com:apache/spark into SPARK-8639
6c18058 [Rosstin] fixed minor typos in docs/README.md and docs/api.md
Follow up of [SPARK-8356](https://issues.apache.org/jira/browse/SPARK-8356) and #6902.
Removes the unit test for the now deprecated ```callUdf```
Unit test in SQLQuerySuite now uses ```udf``` instead of ```callUDF```
Replaced ```callUDF``` by ```udf``` where possible in mllib
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#6993 from BenFradet/SPARK-8575 and squashes the following commits:
26f5a7a [BenFradet] 2 spaces instead of 1
1ddb452 [BenFradet] renamed initUDF in order to be consistent in OneVsRest
48ca15e [BenFradet] used vector type tag for udf call in VectorIndexer
0ebd0da [BenFradet] replace the now deprecated callUDF by udf in VectorIndexer
8013409 [BenFradet] replaced the now deprecated callUDF by udf in Predictor
94345b5 [BenFradet] unifomized udf calls in ProbabilisticClassifier
1305492 [BenFradet] uniformized udf calls in Classifier
a672228 [BenFradet] uniformized udf calls in OneVsRest
49e4904 [BenFradet] Revert "removal of the unit test for the now deprecated callUdf"
bbdeaf3 [BenFradet] fixed syntax for init udf in OneVsRest
fe2a10b [BenFradet] callUDF => udf in ProbabilisticClassifier
0ea30b3 [BenFradet] callUDF => udf in Classifier where possible
197ec82 [BenFradet] callUDF => udf in OneVsRest
84d6780 [BenFradet] modified unit test in SQLQuerySuite to use udf instead of callUDF
477709f [BenFradet] removal of the unit test for the now deprecated callUdf
Python support for Power Iteration Clustering
https://issues.apache.org/jira/browse/SPARK-5962
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#6992 from yanboliang/pyspark-pic and squashes the following commits:
6b03d82 [Yanbo Liang] address comments
4be4423 [Yanbo Liang] Python support for Power Iteration Clustering
Support mining of ordered frequent item sequences.
Author: Feynman Liang <fliang@databricks.com>
Closes#6997 from feynmanliang/fp-sequence and squashes the following commits:
7c14e15 [Feynman Liang] Improve scalatests with R code and Seq
0d3e4b6 [Feynman Liang] Fix python test
ce987cb [Feynman Liang] Backwards compatibility aux constructor
34ef8f2 [Feynman Liang] Fix failing test due to reverse orderering
f04bd50 [Feynman Liang] Naming, add ordered to FreqItemsets, test ordering using Seq
648d4d4 [Feynman Liang] Test case for frequent item sequences
252a36a [Feynman Liang] Add sequence learning flag
Spark's tests currently depend on `mockito-all`, which bundles Hamcrest and Objenesis classes. Instead, it should depend on `mockito-core`, which declares those libraries as Maven dependencies. This is necessary in order to fix a dependency conflict that leads to a NoSuchMethodError when using certain Hamcrest matchers.
See https://github.com/mockito/mockito/wiki/Declaring-mockito-dependency for more details.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7061 from JoshRosen/mockito-core-instead-of-all and squashes the following commits:
70eccbe [Josh Rosen] Depend on mockito-core instead of mockito-all.
Add a param to disable linear feature scaling (to be implemented later in linear & logistic regression). Done as a seperate PR so we can use same param & not conflict while working on the sub-tasks.
Author: Holden Karau <holden@pigscanfly.ca>
Closes#7024 from holdenk/SPARK-8522-Disable-Linear_featureScaling-Spark-8613-Add-param and squashes the following commits:
ce8931a [Holden Karau] Regenerate the sharedParams code
fa6427e [Holden Karau] update text for standardization param.
7b24a2b [Holden Karau] generate the new standardization param
3c190af [Holden Karau] Add the standardization param to sharedparamscodegen
Keep the same naming conventions for PythonMLLibAPI.
Only the following three functions is different from others
```scala
trainNaiveBayes
trainGaussianMixture
trainWord2Vec
```
So change them to
```scala
trainNaiveBayesModel
trainGaussianMixtureModel
trainWord2VecModel
```
It does not affect any users and public APIs, only to make better understand for developer and code hacker.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7011 from yanboliang/py-mllib-api-rename and squashes the following commits:
771ffec [Yanbo Liang] rename some functions of PythonMLLibAPI
fix LabeledPoint parser when there is a whitespace between label and features vector, e.g.
(y, [x1, x2, x3])
Author: Oleksiy Dyagilev <oleksiy_dyagilev@epam.com>
Closes#6954 from fe2s/SPARK-8525 and squashes the following commits:
0755b9d [Oleksiy Dyagilev] [SPARK-8525][MLLIB] addressing comment, removing dep on commons-lang
c1abc2b [Oleksiy Dyagilev] [SPARK-8525][MLLIB] fix LabeledPoint parser when there is a whitespace on specific position
It is useful to generate linear data for easy testing of linear models and in general. Scala already has it. This is just a wrapper around the Scala code.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6715 from MechCoder/generate_linear_input and squashes the following commits:
6182884 [MechCoder] Minor changes
8bda047 [MechCoder] Minor style fixes
0f1053c [MechCoder] [SPARK-8265] Add LinearDataGenerator to pyspark.mllib.utils
Author: Holden Karau <holden@pigscanfly.ca>
Closes#6927 from holdenk/SPARK-7888-Be-able-to-disable-intercept-in-Linear-Regression-in-ML-package and squashes the following commits:
0ad384c [Holden Karau] Add MiMa excludes
4016fac [Holden Karau] Switch to wild card import, remove extra blank lines
ae5baa8 [Holden Karau] CR feedback, move the fitIntercept down rather than changing ymean and etc above
f34971c [Holden Karau] Fix some more long lines
319bd3f [Holden Karau] Fix long lines
3bb9ee1 [Holden Karau] Update the regression suite tests
7015b9f [Holden Karau] Our code performs the same with R, except we need more than one data point but that seems reasonable
0b0c8c0 [Holden Karau] fix the issue with the sample R code
e2140ba [Holden Karau] Add a test, it fails!
5e84a0b [Holden Karau] Write out thoughts and use the correct trait
91ffc0a [Holden Karau] more murh
006246c [Holden Karau] murp?
Author: Holden Karau <holden@pigscanfly.ca>
Closes#6331 from holdenk/SPARK-7781-GradientBoostedTrees.trainRegressor-missing-max-bins and squashes the following commits:
2894695 [Holden Karau] remove extra blank line
2573e8d [Holden Karau] Update the scala side of the pythonmllibapi and make the test a bit nicer too
3a09170 [Holden Karau] add maxBins to to the train method as well
af7f274 [Holden Karau] Add maxBins to GradientBoostedTrees.trainRegressor and correctly mention the default of 32 in other places where it mentioned 100
Implementation of n-gram feature transformer for ML.
Author: Feynman Liang <fliang@databricks.com>
Closes#6887 from feynmanliang/ngram-featurizer and squashes the following commits:
d2c839f [Feynman Liang] Make n > input length yield empty output
9fadd36 [Feynman Liang] Add empty and corner test cases, fix names and spaces
fe93873 [Feynman Liang] Implement n-gram feature transformer
Updated `Attribute.fromStructField` to allow any `NumericType`, rather than just `DoubleType`, and added unit tests for a few of the other NumericTypes.
Author: Mike Dusenberry <dusenberrymw@gmail.com>
Closes#6540 from dusenberrymw/SPARK-7426_AttributeFactory.fromStructField_Should_Allow_NumericTypes and squashes the following commits:
87fecb3 [Mike Dusenberry] Updated Attribute.fromStructField to allow any NumericType, rather than just DoubleType, and added unit tests for a few of the other NumericTypes.
Python API for PCA and PCAModel
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#6315 from yanboliang/spark-7604 and squashes the following commits:
1d58734 [Yanbo Liang] remove transform() in PCAModel, use default behavior
4d9d121 [Yanbo Liang] Python API for PCA and PCAModel
JIRA: https://issues.apache.org/jira/browse/SPARK-8468
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6905 from viirya/cv_min and squashes the following commits:
930d3db [Liang-Chi Hsieh] Fix python unit test and add document.
d632135 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cv_min
16e3b2c [Liang-Chi Hsieh] Take the negative instead of reciprocal.
c3dd8d9 [Liang-Chi Hsieh] For comments.
b5f52c1 [Liang-Chi Hsieh] Add param to CrossValidator for choosing whether to maximize evaulation value.
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
Python API for org.apache.spark.mllib.feature.ElementwiseProduct
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6346 from MechCoder/spark-7605 and squashes the following commits:
79d1ef5 [MechCoder] Consistent and support list / array types
5f81d81 [MechCoder] [SPARK-7605] [MLlib] Python API for ElementwiseProduct
MatrixUDT was recently coded in scala. This has been ported to PySpark
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6354 from MechCoder/spark-6390 and squashes the following commits:
fc4dc1e [MechCoder] Better error message
c940a44 [MechCoder] Added test
aa9c391 [MechCoder] Add pyUDT to MatrixUDT
62a2a7d [MechCoder] [SPARK-6390] Port MatrixUDT to PySpark
Check then make the MLlib Python classification and regression doc to be as complete as the Scala doc.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#6460 from yanboliang/spark-7916 and squashes the following commits:
f8deda4 [Yanbo Liang] trigger jenkins
6dc4d99 [Yanbo Liang] address comments
ce2a43e [Yanbo Liang] truncate too long line and remove extra sparse
3eaf6ad [Yanbo Liang] MLlib Python doc parity check for classification and regression
MLUtils.appendBias method is heavily used in creating intercepts for linear models.
This method uses Breeze's vector concatenation which is very slow compared to the plain
System.arrayCopy. This improvement is to change the implementation to use System.arrayCopy.
I saw the following performance improvements after the change:
Benchmark with mnist dataset for 50 times:
MLUtils.appendBias (SparseVector Before): 47320 ms
MLUtils.appendBias (SparseVector After): 1935 ms
MLUtils.appendBias (DenseVector Before): 5340 ms
MLUtils.appendBias (DenseVector After): 4080 ms
This is almost a 24 times performance boost for SparseVectors.
Author: Roger Menezes <rmenezes@netflix.com>
Closes#6768 from rogermenezes/improve-append-bias and squashes the following commits:
4e42f75 [Roger Menezes] address feedback
e999d79 [Roger Menezes] first commit
Test cases for both StreamingLinearRegression and StreamingLogisticRegression, and code fix.
Edit:
This contribution is my original work and I license the work to the project under the project's open source license.
Author: Paavo <pparkkin@gmail.com>
Closes#6713 from pparkkin/streamingmodel-empty-rdd and squashes the following commits:
ff5cd78 [Paavo] Update strings to use interpolation.
db234cf [Paavo] Use !rdd.isEmpty.
54ad89e [Paavo] Test case for empty stream.
393e36f [Paavo] Ignore empty RDDs.
0bfc365 [Paavo] Test case for empty stream.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6720 from MechCoder/empty_model_check and squashes the following commits:
3a07de5 [MechCoder] Remove construct to get weights in StreamingLinearAlgorithm
This makes the constructor callable in Python. dbtsai
Author: Xiangrui Meng <meng@databricks.com>
Closes#6709 from mengxr/SPARK-8168 and squashes the following commits:
f871de4 [Xiangrui Meng] Add Python friendly constructor to PipelineModel
1. Prevent creating a map of data to find numFeatures
2. If model is empty, then initialize with a zero vector of numFeature
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6684 from MechCoder/spark-8140 and squashes the following commits:
7fbf5f9 [MechCoder] [SPARK-8140] Remove empty model check in StreamingLinearAlgorithm And other minor cosmits
Python API for KernelDensity
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6387 from MechCoder/spark-7639 and squashes the following commits:
17abc62 [MechCoder] add tests
2de6540 [MechCoder] style tests
bf4acc0 [MechCoder] Added doctests
84359d5 [MechCoder] [SPARK-7639] Python API for KernelDensity
Added stats from cross validation as a val in the cross validation model to save them for user access.
Author: leahmcguire <lmcguire@salesforce.com>
Closes#5915 from leahmcguire/saveCVmetrics and squashes the following commits:
49b507b [leahmcguire] fixed tyle error
67537b1 [leahmcguire] rebased
85907f0 [leahmcguire] fixed name
59987cc [leahmcguire] changed param name and test according to comments
36e71e3 [leahmcguire] rebasing
4b8223e [leahmcguire] fixed name
4ddffc6 [leahmcguire] changed param name and test according to comments
3a995da [leahmcguire] Added stats from cross validation as a val in the cross validation model to save them for user access
This is just a workaround to a bigger problem. Some pipeline stages may not be effective during prediction, and they should not complain about missing required columns, e.g. `StringIndexerModel`. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6595 from mengxr/SPARK-8051 and squashes the following commits:
b6a36b9 [Xiangrui Meng] add doc
f143fd4 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-8051
8ee7c7e [Xiangrui Meng] use SparkFunSuite
e112394 [Xiangrui Meng] make StringIndexerModel silent if input column does not exist
Java-friendly APIs added:
* GaussianMixture.run()
* GaussianMixtureModel.predict()
* DistributedLDAModel.javaTopicDistributions()
* StreamingKMeans: trainOn, predictOn, predictOnValues
* Statistics.corr
* params
* added doc to w() since Java docs do not inherit doc
* removed non-Java-friendly w() from StringArrayParam and DoubleArrayParam
* made DoubleArrayParam Java-friendly w() actually Java-friendly
I generated the doc and verified all changes.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6562 from jkbradley/java-api-1.4 and squashes the following commits:
c16821b [Joseph K. Bradley] Small fixes based on code review.
d955581 [Joseph K. Bradley] unit test fixes
29b6b0d [Joseph K. Bradley] small fixes
fe6dcfe [Joseph K. Bradley] Added several Java-friendly APIs + unit tests: NaiveBayes, GaussianMixture, LDA, StreamingKMeans, Statistics.corr, params
Author: Patrick Wendell <patrick@databricks.com>
Closes#6328 from pwendell/spark-1.5-update and squashes the following commits:
2f42d02 [Patrick Wendell] A few more excludes
4bebcf0 [Patrick Wendell] Update to RC4
61aaf46 [Patrick Wendell] Using new release candidate
55f1610 [Patrick Wendell] Another exclude
04b4f04 [Patrick Wendell] More issues with transient 1.4 changes
36f549b [Patrick Wendell] [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0
jira: https://issues.apache.org/jira/browse/SPARK-7983
Customers frequently use zero-based indices in their LIBSVM files. No warnings or errors from Spark will be reported during their computation afterwards, and usually it will lead to wired result for many algorithms (like GBDT).
add a quick check.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6538 from hhbyyh/loadSVM and squashes the following commits:
79d9c11 [Yuhao Yang] optimization as respond to comments
4310710 [Yuhao Yang] merge conflict
96460f1 [Yuhao Yang] merge conflict
20a2811 [Yuhao Yang] use require
6e4f8ca [Yuhao Yang] add check for ascending order
9956365 [Yuhao Yang] add ut for 0-based loadlibsvm exception
5bd1f9a [Yuhao Yang] add require for one-based in loadLIBSVM
I searched the Spark codebase for all occurrences of "scalingVector"
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6596 from jkbradley/scalingVec-rename and squashes the following commits:
d3812f8 [Joseph K. Bradley] renamed scalingVector to scalingVec
This patch significantly refactors CatalystTypeConverters to both clean up the code and enable these conversions to work with future Project Tungsten features.
At a high level, I've reorganized the code so that all functions dealing with the same type are grouped together into type-specific subclasses of `CatalystTypeConveter`. In addition, I've added new methods that allow the Catalyst Row -> Scala Row conversions to access the Catalyst row's fields through type-specific `getTYPE()` methods rather than the generic `get()` / `Row.apply` methods. This refactoring is a blocker to being able to unit test new operators that I'm developing as part of Project Tungsten, since those operators may output `UnsafeRow` instances which don't support the generic `get()`.
The stricter type usage of types here has uncovered some bugs in other parts of Spark SQL:
- #6217: DescribeCommand is assigned wrong output attributes in SparkStrategies
- #6218: DataFrame.describe() should cast all aggregates to String
- #6400: Use output schema, not relation schema, for data source input conversion
Spark SQL current has undefined behavior for what happens when you try to create a DataFrame from user-specified rows whose values don't match the declared schema. According to the `createDataFrame()` Scaladoc:
> It is important to make sure that the structure of every [[Row]] of the provided RDD matches the provided schema. Otherwise, there will be runtime exception.
Given this, it sounds like it's technically not a break of our API contract to fail-fast when the data types don't match. However, there appear to be many cases where we don't fail even though the types don't match. For example, `JavaHashingTFSuite.hasingTF` passes a column of integers values for a "label" column which is supposed to contain floats. This column isn't actually read or modified as part of query processing, so its actual concrete type doesn't seem to matter. In other cases, there could be situations where we have generic numeric aggregates that tolerate being called with different numeric types than the schema specified, but this can be okay due to numeric conversions.
In the long run, we will probably want to come up with precise semantics for implicit type conversions / widening when converting Java / Scala rows to Catalyst rows. Until then, though, I think that failing fast with a ClassCastException is a reasonable behavior; this is the approach taken in this patch. Note that certain optimizations in the inbound conversion functions for primitive types mean that we'll probably preserve the old undefined behavior in a majority of cases.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6222 from JoshRosen/catalyst-converters-refactoring and squashes the following commits:
740341b [Josh Rosen] Optimize method dispatch for primitive type conversions
befc613 [Josh Rosen] Add tests to document Option-handling behavior.
5989593 [Josh Rosen] Use new SparkFunSuite base in CatalystTypeConvertersSuite
6edf7f8 [Josh Rosen] Re-add convertToScala(), since a Hive test still needs it
3f7b2d8 [Josh Rosen] Initialize converters lazily so that the attributes are resolved first
6ad0ebb [Josh Rosen] Fix JavaHashingTFSuite ClassCastException
677ff27 [Josh Rosen] Fix null handling bug; add tests.
8033d4c [Josh Rosen] Fix serialization error in UserDefinedGenerator.
85bba9d [Josh Rosen] Fix wrong input data in InMemoryColumnarQuerySuite
9c0e4e1 [Josh Rosen] Remove last use of convertToScala().
ae3278d [Josh Rosen] Throw ClassCastException errors during inbound conversions.
7ca7fcb [Josh Rosen] Comments and cleanup
1e87a45 [Josh Rosen] WIP refactoring of CatalystTypeConverters
This is scala example code for both linear and logistic regression. Python and Java versions are to be added.
Author: DB Tsai <dbt@netflix.com>
Closes#6576 from dbtsai/elasticNetExample and squashes the following commits:
e7ca406 [DB Tsai] fix test
6bb6d77 [DB Tsai] fix suite and remove duplicated setMaxIter
136e0dd [DB Tsai] address feedback
1ec29d4 [DB Tsai] fix style
9462f5f [DB Tsai] add example
The temporary column should be dropped after we get the prediction column. harsha2010
Author: Xiangrui Meng <meng@databricks.com>
Closes#6592 from mengxr/SPARK-8049 and squashes the following commits:
1d89107 [Xiangrui Meng] use SparkFunSuite
6ee70de [Xiangrui Meng] drop tmp col from OneVsRest output
Updating ML Doc's *"Estimator, Transformer, and Param"* example to use `model.extractParamMap` instead of `model.fittingParamMap`, which no longer exists.
mengxr, I believe this addresses (part of) the *update documentation* TODO list item from [PR 5820](https://github.com/apache/spark/pull/5820).
Author: Mike Dusenberry <dusenberrymw@gmail.com>
Closes#6514 from dusenberrymw/Fix_ML_Doc_Estimator_Transformer_Param_Example and squashes the following commits:
6366e1f [Mike Dusenberry] Updating instances of model.extractParamMap to model.parent.extractParamMap, since the Params of the parent Estimator could possibly differ from thos of the Model.
d850e0e [Mike Dusenberry] Removing all references to "fittingParamMap" throughout Spark, since it has been removed.
0480304 [Mike Dusenberry] Updating the ML Doc "Estimator, Transformer, and Param" Java example to use model.extractParamMap() instead of model.fittingParamMap(), which no longer exists.
7d34939 [Mike Dusenberry] Updating ML Doc "Estimator, Transformer, and Param" example to use model.extractParamMap instead of model.fittingParamMap, which no longer exists.
This PR adds a Java unit test and user guide for `StringIndexer`. I put it before `OneHotEncoder` because they are closely related. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6561 from mengxr/SPARK-7582 and squashes the following commits:
4bba4f1 [Xiangrui Meng] fix example
ba1cd1b [Xiangrui Meng] fix style
7fa18d1 [Xiangrui Meng] add user guide for StringIndexer
136cb93 [Xiangrui Meng] add a Java unit test for StringIndexer
This PR adds a section in the user guide for `VectorAssembler` with code examples in Python/Java/Scala. It also adds a unit test in Java.
jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6556 from mengxr/SPARK-7584 and squashes the following commits:
11313f6 [Xiangrui Meng] simplify Java example
0cd47f3 [Xiangrui Meng] update user guide
fd36292 [Xiangrui Meng] update Java unit test
ce61ca0 [Xiangrui Meng] add Java unit test for VectorAssembler
e399942 [Xiangrui Meng] scala/python example code
Author: Reynold Xin <rxin@databricks.com>
Closes#6534 from rxin/whitespace-mllib and squashes the following commits:
38926e3 [Reynold Xin] [SPARK-3850] Trim trailing spaces for MLlib.
The MLlib ChiSqSelector class is not serializable, and so the example in the ChiSqSelector documentation fails. Also, that example is missing the import of ChiSqSelector.
This PR makes ChiSqSelector extend Serializable in MLlib, and adds the ChiSqSelector import statement to the associated example in the documentation.
Author: Mike Dusenberry <dusenberrymw@gmail.com>
Closes#6462 from dusenberrymw/Make_ChiSqSelector_Serializable_and_Fix_Related_Docs_Example and squashes the following commits:
9cb2f94 [Mike Dusenberry] Make MLlib ChiSqSelector Serializable.
d9003bf [Mike Dusenberry] Add missing import in MLlib ChiSqSelector Docs Scala example.
This patch fixes a build break in maven caused by #6441.
Note that this patch reverts the changes in flume-sink because
this module does not currently depend on Spark core, but the
tests require it. There is not an easy way to make this work
because mvn test dependencies are not transitive (MNG-1378).
For now, we will leave the one test suite in flume-sink out
until we figure out a better solution. This patch is mainly
intended to unbreak the maven build.
Author: Andrew Or <andrew@databricks.com>
Closes#6511 from andrewor14/fix-build-mvn and squashes the following commits:
3d53643 [Andrew Or] [HOT FIX#6441] Fix maven build failures
Right now `unit-tests.log` are not of much value because we can't tell where the test boundaries are easily. This patch adds log statements before and after each test to outline the test boundaries, e.g.:
```
===== TEST OUTPUT FOR o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' =====
15/05/27 12:36:39.596 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO SparkContext: Starting job: count at KryoSerializerSuite.scala:230
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Got job 3 (count at KryoSerializerSuite.scala:230) with 4 output partitions (allowLocal=false)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Final stage: ResultStage 3(count at KryoSerializerSuite.scala:230)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Parents of final stage: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Missing parents: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Submitting ResultStage 3 (ParallelCollectionRDD[5] at parallelize at KryoSerializerSuite.scala:230), which has no missing parents
...
15/05/27 12:36:39.624 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO DAGScheduler: Job 3 finished: count at KryoSerializerSuite.scala:230, took 0.028563 s
15/05/27 12:36:39.625 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO KryoSerializerSuite:
***** FINISHED o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' *****
...
```
Author: Andrew Or <andrew@databricks.com>
Closes#6441 from andrewor14/demarcate-tests and squashes the following commits:
879b060 [Andrew Or] Fix compile after rebase
d622af7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
017c8ba [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
7790b6c [Andrew Or] Fix tests after logical merge conflict
c7460c0 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
c43ffc4 [Andrew Or] Fix tests?
8882581 [Andrew Or] Fix tests
ee22cda [Andrew Or] Fix log message
fa9450e [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
12d1e1b [Andrew Or] Various whitespace changes (minor)
69cbb24 [Andrew Or] Make all test suites extend SparkFunSuite instead of FunSuite
bbce12e [Andrew Or] Fix manual things that cannot be covered through automation
da0b12f [Andrew Or] Add core tests as dependencies in all modules
f7d29ce [Andrew Or] Introduce base abstract class for all test suites
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6497 from MechCoder/spark-7946 and squashes the following commits:
2fdd0a3 [MechCoder] Add non-regression test
8c988c6 [MechCoder] [SPARK-7946] DecayFactor wrongly set in StreamingKMeans
This PR contains two major changes to `OneHotEncoder`:
1. more robust handling of ML attributes. If the input attribute is unknown, we look at the values to get the max category index
2. change `includeFirst` to `dropLast` and leave the default to `true`. There are couple benefits:
a. consistent with other tutorials of one-hot encoding (or dummy coding) (e.g., http://www.ats.ucla.edu/stat/mult_pkg/faq/general/dummy.htm)
b. keep the indices unmodified in the output vector. If we drop the first, all indices will be shifted by 1.
c. If users use `StringIndex`, the last element is the least frequent one.
Sorry for including two changes in one PR! I'll update the user guide in another PR.
jkbradley sryza
Author: Xiangrui Meng <meng@databricks.com>
Closes#6466 from mengxr/SPARK-7912 and squashes the following commits:
a280dca [Xiangrui Meng] fix tests
d8f234d [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7912
171b276 [Xiangrui Meng] mention the difference between our impl vs sklearn's
00dfd96 [Xiangrui Meng] update OneHotEncoder in Python
208ddad [Xiangrui Meng] update OneHotEncoder to handle ML attributes and change includeFirst to dropLast
Expose user/item factors in DataFrames. This is to be more consistent with the pipeline API. It also helps maintain consistent APIs across languages. This PR also removed fitting params from `ALSModel`.
coderxiang
Author: Xiangrui Meng <meng@databricks.com>
Closes#6468 from mengxr/SPARK-7922 and squashes the following commits:
7bfb1d5 [Xiangrui Meng] update ALSModel in PySpark
1ba5607 [Xiangrui Meng] use DataFrames for user/item factors in ALS
`VectorAssembler` should carry over ML attributes. For unknown attributes, we assume numeric values. This PR handles the following cases:
1. DoubleType with ML attribute: carry over
2. DoubleType without ML attribute: numeric value
3. Scalar type: numeric value
4. VectorType with all ML attributes: carry over and update names
5. VectorType with number of ML attributes: assume all numeric
6. VectorType without ML attributes: check the first row and get the number of attributes
jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6452 from mengxr/SPARK-7198 and squashes the following commits:
a9d2469 [Xiangrui Meng] add space
facdb1f [Xiangrui Meng] VectorAssembler should output ML attributes
~~A PythonUDT shouldn't be serialized into external Scala types in PythonRDD. I'm not sure whether this should fix one of the bugs related to SQL UDT/UDF in PySpark.~~
The fix above didn't work. So I added a workaround for this. If a Python UDF is applied to a Python UDT. This will put the Python SQL types as inputs. Still incorrect, but at least it doesn't throw exceptions on the Scala side. davies harsha2010
Author: Xiangrui Meng <meng@databricks.com>
Closes#6442 from mengxr/SPARK-7903 and squashes the following commits:
c257d2a [Xiangrui Meng] add a workaround for VectorUDT
With descent coverage of feature transformers, algorithms, and model tuning support, it is time to graduate `spark.ml` from alpha. This PR changes all `AlphaComponent` annotations to either `DeveloperApi` or `Experimental`, depending on whether we expect a class/method to be used by end users (who use the pipeline API to assemble/tune their ML pipelines but not to create new pipeline components.) `UnaryTransformer` becomes a `DeveloperApi` in this PR.
jkbradley harsha2010
Author: Xiangrui Meng <meng@databricks.com>
Closes#6417 from mengxr/SPARK-7748 and squashes the following commits:
effbccd [Xiangrui Meng] organize imports
c15028e [Xiangrui Meng] added missing docs
1b2e5f8 [Xiangrui Meng] update package doc
73ca791 [Xiangrui Meng] alpha -> ex/dev for the rest
93819db [Xiangrui Meng] alpha -> ex/dev in ml.param
55ca073 [Xiangrui Meng] alpha -> ex/dev in ml.feature
83572f1 [Xiangrui Meng] add Experimental and DeveloperApi tags (wip)
The densities in KernelDensity are scaled down by
(number of parallel processes X number of points). It should be just no.of samples. This results in broken tests in KernelDensitySuite which haven't been tested properly.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6383 from MechCoder/spark-7844 and squashes the following commits:
ab81302 [MechCoder] Math->math
9b8ed50 [MechCoder] Make one pass to update count
a92fe50 [MechCoder] [SPARK-7844] Fix broken tests in KernelDensity
Added user guide sections with code examples.
Also added small Java unit tests to test Java example in guide.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6127 from jkbradley/feature-guide-2 and squashes the following commits:
cd47f4b [Joseph K. Bradley] Updated based on code review
f16bcec [Joseph K. Bradley] Fixed merge issues and update Python examples print calls for Python 3
0a862f9 [Joseph K. Bradley] Added Normalizer, StandardScaler to ml-features doc, plus small Java unit tests
a21c2d6 [Joseph K. Bradley] Updated ml-features.md with IDF
This PR updates `HashingTF` to output ML attributes that tell the number of features in the output column. We need to expand `UnaryTransformer` to support output metadata. A `df outputMetadata: Metadata` is not sufficient because the metadata may also depends on the input data. Though this is not true for `HashingTF`, I think it is reasonable to update `UnaryTransformer` in a separate PR. `checkParams` is added to verify common requirements for params. I will send a separate PR to use it in other test suites. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6308 from mengxr/SPARK-7219 and squashes the following commits:
9bd2922 [Xiangrui Meng] address comments
e82a68a [Xiangrui Meng] remove sqlContext from test suite
995535b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7219
2194703 [Xiangrui Meng] add test for attributes
178ae23 [Xiangrui Meng] update HashingTF with tests
91a6106 [Xiangrui Meng] WIP
The previous default is `{gaps: false, pattern: "\\p{L}+|[^\\p{L}\\s]+"}`. The default pattern is hard to understand. This PR changes the default to `{gaps: true, pattern: "\\s+"}`. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6330 from mengxr/SPARK-7794 and squashes the following commits:
5ee7cde [Xiangrui Meng] update RegexTokenizer default settings
We removed `varargs` due to Java compilation issues. That was a false alarm because I didn't run `build/sbt clean`. So this PR reverts the changes. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6320 from mengxr/SPARK-7498 and squashes the following commits:
74a7259 [Xiangrui Meng] add varargs back to setDefault
Added VectorIndexer section to ML user guide. Also added javaCategoryMaps() method and Java unit test for it.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6255 from jkbradley/vector-indexer-guide and squashes the following commits:
dbb8c4c [Joseph K. Bradley] simplified VectorIndexerModel.javaCategoryMaps
f692084 [Joseph K. Bradley] Added VectorIndexer section to ML user guide. Also added javaCategoryMaps() method and Java unit test for it.
same issue and fix as in Spark-7694.
Author: Shuo Xiang <shuoxiangpub@gmail.com>
Closes#6321 from coderxiang/nb and squashes the following commits:
a5e6de4 [Shuo Xiang] use getOrElse for svmmodel.tostring
2cb0177 [Shuo Xiang] Merge remote-tracking branch 'upstream/master' into nb
5f109b4 [Shuo Xiang] Merge remote-tracking branch 'upstream/master'
c5c5bfe [Shuo Xiang] Merge remote-tracking branch 'upstream/master'
98804c9 [Shuo Xiang] fix bug in topBykey and update test
to be consistent with other string names in MLlib. This PR also updates the implementation to use vals instead of hardcoded strings. jkbradley leahmcguire
Author: Xiangrui Meng <meng@databricks.com>
Closes#6277 from mengxr/SPARK-7752 and squashes the following commits:
f38b662 [Xiangrui Meng] add another case _ back in test
ae5c66a [Xiangrui Meng] model type -> modelType
711d1c6 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7752
40ae53e [Xiangrui Meng] fix Java test suite
264a814 [Xiangrui Meng] add case _ back
3c456a8 [Xiangrui Meng] update NB user guide
17bba53 [Xiangrui Meng] update naive Bayes to use lowercase model type strings
Update `KernelDensity` API to make it extensible to different kernels in the future. `bandwidth` is used instead of `standardDeviation`. The static `kernelDensity` method is removed from `Statistics`. The implementation is updated using BLAS, while the algorithm remains the same. sryza srowen
Author: Xiangrui Meng <meng@databricks.com>
Closes#6279 from mengxr/SPARK-7753 and squashes the following commits:
4cdfadc [Xiangrui Meng] add example code in the doc
767fd5a [Xiangrui Meng] update KernelDensity API
to simplify test suites that require a SQLContext.
Author: Xiangrui Meng <meng@databricks.com>
Closes#6303 from mengxr/SPARK-7774 and squashes the following commits:
0622b5a [Xiangrui Meng] update some other test suites
e1f9b8d [Xiangrui Meng] add sqlContext to MLlibTestSparkContext
Set a default value for `outputCol` instead of forcing users to name it. This is useful for intermediate transformers in the pipeline. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6289 from mengxr/SPARK-7762 and squashes the following commits:
54edebc [Xiangrui Meng] merge master
bff8667 [Xiangrui Meng] update unit test
171246b [Xiangrui Meng] add unit test for outputCol
a4321bd [Xiangrui Meng] set default value for outputCol
Minor updates to the spark.mllib APIs:
1. Add `DeveloperApi` to `PMMLExportable` and add `Experimental` to `toPMML` methods.
2. Mention `RankingMetrics.of` in the `RankingMetrics` constructor.
Author: Xiangrui Meng <meng@databricks.com>
Closes#6280 from mengxr/SPARK-7537 and squashes the following commits:
1bd2583 [Xiangrui Meng] organize imports
94afa7a [Xiangrui Meng] mark all toPMML methods experimental
4c40da1 [Xiangrui Meng] mention the factory method for RankingMetrics for Java users
88c62d0 [Xiangrui Meng] add DeveloperApi to PMMLExportable
Add MultilabelMetrics in PySpark/MLlib
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#6276 from yanboliang/spark-6094 and squashes the following commits:
b8e3343 [Yanbo Liang] Add MultilabelMetrics in PySpark/MLlib
JIRA issue [link](https://issues.apache.org/jira/browse/SPARK-7663).
We should check the model size of word2vec, to prevent the unexpected empty.
CC srowen.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#6228 from yinxusen/SPARK-7663 and squashes the following commits:
21770c5 [Xusen Yin] check the vocab size
54ae63e [Xusen Yin] add requirement for word2vec model
CC jkbradley.
JIRA [issue](https://issues.apache.org/jira/browse/SPARK-7586).
Author: Xusen Yin <yinxusen@gmail.com>
Closes#6181 from yinxusen/SPARK-7586 and squashes the following commits:
77014c5 [Xusen Yin] comment fix
57a4c07 [Xusen Yin] small fix for docs
1178c8f [Xusen Yin] remove the correctness check in java suite
1c3f389 [Xusen Yin] delete sbt commit
1af152b [Xusen Yin] check python example code
1b5369e [Xusen Yin] add docs of word2vec
Changed shared param HasSeed to have default based on hashCode of class name, instead of random number.
Also, removed fixed random seeds from Word2Vec and ALS.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6251 from jkbradley/scala-fixed-seed and squashes the following commits:
0e37184 [Joseph K. Bradley] Fixed Word2VecSuite, ALSSuite in spark.ml to use original fixed random seeds
678ec3a [Joseph K. Bradley] Removed fixed random seeds from Word2Vec and ALS. Changed shared param HasSeed to have default based on hashCode of class name, instead of random number.
Made Model.parent transient. Added Model.hasParent to test for null parent
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5914 from jkbradley/parent-optional and squashes the following commits:
d501774 [Joseph K. Bradley] Made Model.parent transient. Added Model.hasParent to test for null parent
JIRA [here](https://issues.apache.org/jira/browse/SPARK-7581).
CC jkbradley
Author: Xusen Yin <yinxusen@gmail.com>
Closes#6113 from yinxusen/SPARK-7581 and squashes the following commits:
1a7d80d [Xusen Yin] merge with master
892a8e9 [Xusen Yin] fix python 3 compatibility
ec935bf [Xusen Yin] small fix
3e9fa1d [Xusen Yin] delete note
69fcf85 [Xusen Yin] simplify and add python example
81d21dc [Xusen Yin] add programming guide for Polynomial Expansion
40babfb [Xusen Yin] add java test suite for PolynomialExpansion
