| Commit message (Collapse) | Author | Age | Files | Lines |
|
|
|
|
|
|
|
|
|
| |
Reinstated LogisticRegression.threshold Param for binary compatibility. Param thresholds overrides threshold, if set.
CC: mengxr dbtsai feynmanliang
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #8079 from jkbradley/logreg-reinstate-threshold.
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
explicit param values
From JIRA: Currently, Params.copyValues copies default parameter values to the paramMap of the target instance, rather than the defaultParamMap. It should copy to the defaultParamMap because explicitly setting a parameter can change the semantics.
This issue arose in SPARK-9789, where 2 params "threshold" and "thresholds" for LogisticRegression can have mutually exclusive values. If thresholds is set, then fit() will copy the default value of threshold as well, easily resulting in inconsistent settings for the 2 params.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #8115 from jkbradley/copyvalues-fix.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
1. Add “asymmetricDocConcentration” and revert docConcentration changes. If the (internal) doc concentration vector is a single value, “getDocConcentration" returns it. If it is a constant vector, getDocConcentration returns the first item, and fails otherwise.
2. Give `LDAModel.gammaShape` a default value in `LDAModel` concrete class constructors.
jkbradley
Author: Feynman Liang <fliang@databricks.com>
Closes #8077 from feynmanliang/SPARK-9788 and squashes the following commits:
6b07bc8 [Feynman Liang] Code review changes
9d6a71e [Feynman Liang] Add asymmetricAlpha alias
bf4e685 [Feynman Liang] Asymmetric docConcentration
4cab972 [Feynman Liang] Default gammaShape
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Adds unit test for `equals` on `mllib.linalg.Matrix` class and `equals` to both `SparseMatrix` and `DenseMatrix`. Supports equality testing between `SparseMatrix` and `DenseMatrix`.
mengxr
Author: Feynman Liang <fliang@databricks.com>
Closes #8042 from feynmanliang/SPARK-9750 and squashes the following commits:
bb70d5e [Feynman Liang] Breeze compare for dense matrices as well, in case other is sparse
ab6f3c8 [Feynman Liang] Sparse matrix compare for equals
22782df [Feynman Liang] Add equality based on matrix semantics, not representation
78f9426 [Feynman Liang] Add casts
43d28fa [Feynman Liang] Fix failing test
6416fa0 [Feynman Liang] Add failing sparse matrix equals tests
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
As a precursor to adding a public constructor add an option to handle unseen values by skipping rather than throwing an exception (default remains throwing an exception),
Author: Holden Karau <holden@pigscanfly.ca>
Closes #7266 from holdenk/SPARK-8764-string-indexer-should-take-option-to-handle-unseen-values and squashes the following commits:
38a4de9 [Holden Karau] fix long line
045bf22 [Holden Karau] Add a second b entry so b gets 0 for sure
81dd312 [Holden Karau] Update the docs for handleInvalid param to be more descriptive
7f37f6e [Holden Karau] remove extra space (scala style)
414e249 [Holden Karau] And switch to using handleInvalid instead of skipInvalid
1e53f9b [Holden Karau] update the param (codegen side)
7a22215 [Holden Karau] fix typo
100a39b [Holden Karau] Merge in master
aa5b093 [Holden Karau] Since we filter we should never go down this code path if getSkipInvalid is true
75ffa69 [Holden Karau] Remove extra newline
d69ef5e [Holden Karau] Add a test
b5734be [Holden Karau] Add support for unseen labels
afecd4e [Holden Karau] Add a param to skip invalid entries.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Implements the transforms which are defined by SQL statement.
Currently we only support SQL syntax like 'SELECT ... FROM __THIS__'
where '__THIS__' represents the underlying table of the input dataset.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #7465 from yanboliang/spark-8345 and squashes the following commits:
b403fcb [Yanbo Liang] address comments
0d4bb15 [Yanbo Liang] a better transformSchema() implementation
51eb9e7 [Yanbo Liang] Add an SQL node as a feature transformer
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Resubmit of [https://github.com/apache/spark/pull/6906] for adding single-vec predict to GMMs
CC: dkobylarz mengxr
To be merged with master and branch-1.5
Primary author: dkobylarz
Author: Dariusz Kobylarz <darek.kobylarz@gmail.com>
Closes #8039 from jkbradley/gmm-predict-vec and squashes the following commits:
bfbedc4 [Dariusz Kobylarz] [SPARK-8481] [MLlib] GaussianMixtureModel predict accepting single vector
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
IsotonicRegression
This PR contains the following changes:
* add `featureIndex` to handle vector features (in order to chain isotonic regression easily with output from logistic regression
* make getter/setter names consistent with params
* remove inheritance from Regressor because it is tricky to handle both `DoubleType` and `VectorType`
* simplify test data generation
jkbradley zapletal-martin
Author: Xiangrui Meng <meng@databricks.com>
Closes #7952 from mengxr/SPARK-9493 and squashes the following commits:
8818ac3 [Xiangrui Meng] address comments
05e2216 [Xiangrui Meng] address comments
8d08090 [Xiangrui Meng] add featureIndex to handle vector features make getter/setter names consistent with params remove inheritance from Regressor
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
I have added support for stats in LogisticRegression. The API is similar to that of LinearRegression with LogisticRegressionTrainingSummary and LogisticRegressionSummary
I have some queries and asked them inline.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes #7538 from MechCoder/log_reg_stats and squashes the following commits:
2e9f7c7 [MechCoder] Change defs into lazy vals
d775371 [MechCoder] Clean up class inheritance
9586125 [MechCoder] Add abstraction to handle Multiclass Metrics
40ad8ef [MechCoder] minor
640376a [MechCoder] remove unnecessary dataframe stuff and add docs
80d9954 [MechCoder] Added tests
fbed861 [MechCoder] DataFrame support for metrics
70a0fc4 [MechCoder] [SPARK-9112] [ML] Implement Stats for LogisticRegression
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Add VectorSlicer transformer to spark.ml, with features specified as either indices or names. Transfers feature attributes for selected features.
Updated version of [https://github.com/apache/spark/pull/5731]
CC: yinxusen This updates your PR. You'll still be the primary author of this PR.
CC: mengxr
Author: Xusen Yin <yinxusen@gmail.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #7972 from jkbradley/yinxusen-SPARK-5895 and squashes the following commits:
b16e86e [Joseph K. Bradley] fixed scala style
71c65d2 [Joseph K. Bradley] fix import order
86e9739 [Joseph K. Bradley] cleanups per code review
9d8d6f1 [Joseph K. Bradley] style fix
83bc2e9 [Joseph K. Bradley] Updated VectorSlicer
98c6939 [Xusen Yin] fix style error
ecbf2d3 [Xusen Yin] change interfaces and params
f6be302 [Xusen Yin] Merge branch 'master' into SPARK-5895
e4781f2 [Xusen Yin] fix commit error
fd154d7 [Xusen Yin] add test suite of vector slicer
17171f8 [Xusen Yin] fix slicer
9ab9747 [Xusen Yin] add vector slicer
aa5a0bf [Xusen Yin] add vector slicer
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
This is a major refactoring of the PrefixSpan implementation. It contains the following changes:
1. Expand prefix with one item at a time. The existing implementation generates all subsets for each itemset, which might have scalability issue when the itemset is large.
2. Use a new internal format. `<(12)(31)>` is represented by `[0, 1, 2, 0, 1, 3, 0]` internally. We use `0` because negative numbers are used to indicates partial prefix items, e.g., `_2` is represented by `-2`.
3. Remember the start indices of all partial projections in the projected postfix to help next projection.
4. Reuse the original sequence array for projected postfixes.
5. Use `Prefix` IDs in aggregation rather than its content.
6. Use `ArrayBuilder` for building primitive arrays.
7. Expose `maxLocalProjDBSize`.
8. Tests are not changed except using `0` instead of `-1` as the delimiter.
`Postfix`'s API doc should be a good place to start.
Closes #7594
feynmanliang zhangjiajin
Author: Xiangrui Meng <meng@databricks.com>
Closes #7937 from mengxr/SPARK-9540 and squashes the following commits:
2d0ec31 [Xiangrui Meng] address more comments
48f450c [Xiangrui Meng] address comments from Feynman; fixed a bug in project and added a test
65f90e8 [Xiangrui Meng] naming and documentation
8afc86a [Xiangrui Meng] refactor impl
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
All compressed sensing applications, and some of the regression use-cases will have better result by turning the feature scaling off. However, if we implement this naively by training the dataset without doing any standardization, the rate of convergency will not be good. This can be implemented by still standardizing the training dataset but we penalize each component differently to get effectively the same objective function but a better numerical problem. As a result, for those columns with high variances, they will be penalized less, and vice versa. Without this, since all the features are standardized, so they will be penalized the same.
In R, there is an option for this.
standardize
Logical flag for x variable standardization, prior to fitting the model sequence. The coefficients are always returned on the original scale. Default is standardize=TRUE. If variables are in the same units already, you might not wish to standardize. See details below for y standardization with family="gaussian".
Note that the primary author for this PR is holdenk
Author: Holden Karau <holden@pigscanfly.ca>
Author: DB Tsai <dbt@netflix.com>
Closes #7875 from dbtsai/SPARK-8522 and squashes the following commits:
e856036 [DB Tsai] scala doc
596e96c [DB Tsai] minor
bbff347 [DB Tsai] naming
baa0805 [DB Tsai] touch up
d6234ba [DB Tsai] Merge branch 'master' into SPARK-8522-Disable-Linear_featureScaling-Spark-8601-in-Linear_regression
6b1dc09 [Holden Karau] Merge branch 'master' into SPARK-8522-Disable-Linear_featureScaling-Spark-8601-in-Linear_regression
332f140 [Holden Karau] Merge in master
eebe10a [Holden Karau] Use same comparision operator throughout the test
3f92935 [Holden Karau] merge
b83a41e [Holden Karau] Expand the tests and make them similar to the other PR also providing an option to disable standardization (but for LoR).
0c334a2 [Holden Karau] Remove extra line
99ce053 [Holden Karau] merge in master
e54a8a9 [Holden Karau] Fix long line
e47c574 [Holden Karau] Add support for L2 without standardization.
55d3a66 [Holden Karau] Add standardization param for linear regression
00a1dc5 [Holden Karau] Add the param to the linearregression impl
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
This PR replaces the old "threshold" with a generalized "thresholds" Param. We keep getThreshold,setThreshold for backwards compatibility for binary classification.
Note that the primary author of this PR is holdenk
Author: Holden Karau <holden@pigscanfly.ca>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #7909 from jkbradley/holdenk-SPARK-8069-add-cutoff-aka-threshold-to-random-forest and squashes the following commits:
3952977 [Joseph K. Bradley] fixed pyspark doc test
85febc8 [Joseph K. Bradley] made python unit tests a little more robust
7eb1d86 [Joseph K. Bradley] small cleanups
6cc2ed8 [Joseph K. Bradley] Fixed remaining merge issues.
0255e44 [Joseph K. Bradley] Many cleanups for thresholds, some more tests
7565a60 [Holden Karau] fix pep8 style checks, add a getThreshold method similar to our LogisticRegression.scala one for API compat
be87f26 [Holden Karau] Convert threshold to thresholds in the python code, add specialized support for Array[Double] to shared parems codegen, etc.
6747dad [Holden Karau] Override raw2prediction for ProbabilisticClassifier, fix some tests
25df168 [Holden Karau] Fix handling of thresholds in LogisticRegression
c02d6c0 [Holden Karau] No default for thresholds
5e43628 [Holden Karau] CR feedback and fixed the renamed test
f3fbbd1 [Holden Karau] revert the changes to random forest :(
51f581c [Holden Karau] Add explicit types to public methods, fix long line
f7032eb [Holden Karau] Fix a java test bug, remove some unecessary changes
adf15b4 [Holden Karau] rename the classifier suite test to ProbabilisticClassifierSuite now that we only have it in Probabilistic
398078a [Holden Karau] move the thresholding around a bunch based on the design doc
4893bdc [Holden Karau] Use numtrees of 3 since previous result was tied (one tree for each) and the switch from different max methods picked a different element (since they were equal I think this is ok)
638854c [Holden Karau] Add a scala RandomForestClassifierSuite test based on corresponding python test
e09919c [Holden Karau] Fix return type, I need more coffee....
8d92cac [Holden Karau] Use ClassifierParams as the head
3456ed3 [Holden Karau] Add explicit return types even though just test
a0f3b0c [Holden Karau] scala style fixes
6f14314 [Holden Karau] Since hasthreshold/hasthresholds is in root classifier now
ffc8dab [Holden Karau] Update the sharedParams
0420290 [Holden Karau] Allow us to override the get methods selectively
978e77a [Holden Karau] Move HasThreshold into classifier params and start defining the overloaded getThreshold/getThresholds functions
1433e52 [Holden Karau] Revert "try and hide threshold but chainges the API so no dice there"
1f09a2e [Holden Karau] try and hide threshold but chainges the API so no dice there
efb9084 [Holden Karau] move setThresholds only to where its used
6b34809 [Holden Karau] Add a test with thresholding for the RFCS
74f54c3 [Holden Karau] Fix creation of vote array
1986fa8 [Holden Karau] Setting the thresholds only makes sense if the underlying class hasn't overridden predict, so lets push it down.
2f44b18 [Holden Karau] Add a global default of null for thresholds param
f338cfc [Holden Karau] Wait that wasn't a good idea, Revert "Some progress towards unifying threshold and thresholds"
634b06f [Holden Karau] Some progress towards unifying threshold and thresholds
85c9e01 [Holden Karau] Test passes again... little fnur
099c0f3 [Holden Karau] Move thresholds around some more (set on model not trainer)
0f46836 [Holden Karau] Start adding a classifiersuite
f70eb5e [Holden Karau] Fix test compile issues
a7d59c8 [Holden Karau] Move thresholding into Classifier trait
5d999d2 [Holden Karau] Some more progress, start adding a test (maybe try and see if we can find a better thing to use for the base of the test)
1fed644 [Holden Karau] Use thresholds to scale scores in random forest classifcation
31d6bf2 [Holden Karau] Start threading the threshold info through
0ef228c [Holden Karau] Add hasthresholds
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
warnings, 1.5.0 edition
Enable most javac lint warnings; fix a lot of build warnings. In a few cases, touch up surrounding code in the process.
I'll explain several of the changes inline in comments.
Author: Sean Owen <sowen@cloudera.com>
Closes #7862 from srowen/SPARK-9534 and squashes the following commits:
ea51618 [Sean Owen] Enable most javac lint warnings; fix a lot of build warnings. In a few cases, touch up surrounding code in the process.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Add missing methods
1. getVectors
2. findSynonyms
to W2Vec scala and python API
mengxr
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes #7263 from MechCoder/missing_methods_w2vec and squashes the following commits:
149d5ca [MechCoder] minor doc
69d91b7 [MechCoder] [SPARK-8874] [ML] Add missing methods in Word2Vec
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Regressor
Added featureImportance to RandomForestClassifier and Regressor.
This follows the scikit-learn implementation here: [https://github.com/scikit-learn/scikit-learn/blob/a95203b249c1cf392f86d001ad999e29b2392739/sklearn/tree/_tree.pyx#L3341]
CC: yanboliang Would you mind taking a look? Thanks!
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Feynman Liang <fliang@databricks.com>
Closes #7838 from jkbradley/dt-feature-importance and squashes the following commits:
72a167a [Joseph K. Bradley] fixed unit test
86cea5f [Joseph K. Bradley] Modified RF featuresImportances to return Vector instead of Map
5aa74f0 [Joseph K. Bradley] finally fixed unit test for real
33df5db [Joseph K. Bradley] fix unit test
42a2d3b [Joseph K. Bradley] fix unit test
fe94e72 [Joseph K. Bradley] modified feature importance unit tests
cc693ee [Feynman Liang] Add classifier tests
79a6f87 [Feynman Liang] Compare dense vectors in test
21d01fc [Feynman Liang] Added failing SKLearn test
ac0b254 [Joseph K. Bradley] Added featureImportance to RandomForestClassifier/Regressor. Need to add unit tests
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
ProbabilisticClassifier
RandomForestClassifier now outputs rawPrediction based on tree probabilities, plus probability column computed from normalized rawPrediction.
CC: holdenk
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #7859 from jkbradley/rf-prob and squashes the following commits:
6c28f51 [Joseph K. Bradley] Changed RandomForestClassifier to extend ProbabilisticClassifier
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
1. Use `PrefixSpanModel` to wrap the frequent sequences.
2. Define `FreqSequence` to wrap each frequent sequence, which contains a Java-friendly method `javaSequence`
3. Overload `run` for Java users.
4. Added a unit test in Java to check Java compatibility.
zhangjiajin feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes #7869 from mengxr/SPARK-9527 and squashes the following commits:
4345594 [Xiangrui Meng] add PrefixSpanModel and make PrefixSpan Java friendly
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
mengxr Please review after #7818 merges and master is rebased.
Continues work by rikima
Closes #7400
Author: Feynman Liang <fliang@databricks.com>
Author: masaki rikitoku <rikima3132@gmail.com>
Closes #7837 from feynmanliang/SPARK-7400-genericItems and squashes the following commits:
8b2c756 [Feynman Liang] Remove orig
92443c8 [Feynman Liang] Style fixes
42c6349 [Feynman Liang] Style fix
14e67fc [Feynman Liang] Generic prefixSpan itemtypes
b3b21e0 [Feynman Liang] Initial support for generic itemtype in public api
b86e0d5 [masaki rikitoku] modify to support generic item type
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
jira: https://issues.apache.org/jira/browse/SPARK-8169
stop words: http://en.wikipedia.org/wiki/Stop_words
StopWordsRemover takes a string array column and outputs a string array column with all defined stop words removed. The transformer should also come with a standard set of stop words as default.
Currently I used a minimum stop words set since on some [case](http://nlp.stanford.edu/IR-book/html/htmledition/dropping-common-terms-stop-words-1.html), small set of stop words is preferred.
ASCII char has been tested, Yet I cannot check it in due to style check.
Further thought,
1. Maybe I should use OpenHashSet. Is it recommended?
2. Currently I leave the null in input array untouched, i.e. Array(null, null) => Array(null, null).
3. If the current stop words set looks too limited, any suggestion for replacement? We can have something similar to the one in [SKlearn](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/stop_words.py).
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #6742 from hhbyyh/stopwords and squashes the following commits:
fa959d8 [Yuhao Yang] separating udf
f190217 [Yuhao Yang] replace default list and other small fix
04403ab [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into stopwords
b3aa957 [Yuhao Yang] add stopWordsRemover
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
mengxr Extends PrefixSpan to non-temporal itemsets. Continues work by zhangjiajin
* Internal API uses List[Set[Int]] which is likely not efficient; will need to refactor during QA
Closes #7646
Author: zhangjiajin <zhangjiajin@huawei.com>
Author: Feynman Liang <fliang@databricks.com>
Author: zhang jiajin <zhangjiajin@huawei.com>
Closes #7818 from feynmanliang/SPARK-8999-nonTemporal and squashes the following commits:
4ded81d [Feynman Liang] Replace all filters to filter nonempty
350e67e [Feynman Liang] Code review feedback
03156ca [Feynman Liang] Fix tests, drop delimiters at boundaries of sequences
d1fe0ed [Feynman Liang] Remove comments
86ca4e5 [Feynman Liang] Fix style
7c7bf39 [Feynman Liang] Fixed itemSet sequences
6073b10 [Feynman Liang] Basic itemset functionality, failing test
1a7fb48 [Feynman Liang] Add delimiter to results
5db00aa [Feynman Liang] Working for items, not itemsets
6787716 [Feynman Liang] Working on temporal sequences
f1114b9 [Feynman Liang] Add -1 delimiter
00fe756 [Feynman Liang] Reset base files for rebase
f486dcd [zhangjiajin] change maxLocalProjDBSize and fix a bug (remove -3 from frequent items).
60a0b76 [zhangjiajin] fixed a scala style error.
740c203 [zhangjiajin] fixed a scala style error.
5785cb8 [zhangjiajin] support non-temporal sequence
a5d649d [zhangjiajin] restore original version
09dc409 [zhangjiajin] Merge branch 'master' of https://github.com/apache/spark into multiItems_2
ae8c02d [zhangjiajin] Fixed some Scala style errors.
216ab0c [zhangjiajin] Support non-temporal sequence in PrefixSpan
b572f54 [zhangjiajin] initialize file before rebase.
f06772f [zhangjiajin] fix a scala style error.
a7e50d4 [zhangjiajin] Add feature: Collect enough frequent prefixes before projection in PrefixSpan.
c1d13d0 [zhang jiajin] Delete PrefixspanSuite.scala
d9d8137 [zhang jiajin] Delete Prefixspan.scala
c6ceb63 [zhangjiajin] Add new algorithm PrefixSpan and test file.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
It is useful to convert the encoded indices back to their string representation for result inspection. We can add a function which creates an inverse transformation.
Author: Holden Karau <holden@pigscanfly.ca>
Closes #6339 from holdenk/SPARK-7446-inverse-transform-for-string-indexer and squashes the following commits:
7cdf915 [Holden Karau] scala style comment fix
b9cffb6 [Holden Karau] Update the labels param to have the metadata note
6a38edb [Holden Karau] Setting the default needs to come after the value gets defined
9e241d8 [Holden Karau] use Array.empty
21c8cfa [Holden Karau] Merge branch 'master' into SPARK-7446-inverse-transform-for-string-indexer
64dd3a3 [Holden Karau] Merge branch 'master' into SPARK-7446-inverse-transform-for-string-indexer
4f06c59 [Holden Karau] Fix comment styles, use empty array as the default, etc.
a60c0e3 [Holden Karau] CR feedback (remove old constructor, add a note about use of setLabels)
1987b95 [Holden Karau] Use default copy
71e8d66 [Holden Karau] Make labels a local param for StringIndexerInverse
8450d0b [Holden Karau] Use the labels param in StringIndexerInverse
7464019 [Holden Karau] Add a labels param
868b1a9 [Holden Karau] Update scaladoc since we don't have labelsCol anymore
5aa38bf [Holden Karau] Add an inverse test using only meta data, pass labels when calling inverse method
f3e0c64 [Holden Karau] CR feedback
ebed932 [Holden Karau] Add Experimental tag and some scaladocs. Also don't require that the inputCol has the metadata on it, instead have the labelsCol specified when creating the inverse.
03ebf95 [Holden Karau] Add explicit type for invert function
ecc65e0 [Holden Karau] Read the metadata correctly, use the array, pass the test
a42d773 [Holden Karau] Fix test to supply cols as per new invert method
16cc3c3 [Holden Karau] Add an invert method
d4bcb20 [Holden Karau] Make the inverse string indexer into a transformer (still needs test updates but compiles)
e8bf3ad [Holden Karau] Merge branch 'master' into SPARK-7446-inverse-transform-for-string-indexer
c3fdee1 [Holden Karau] Some WIP refactoring based on jkbradley's CR feedback. Definite work-in-progress
557bef8 [Holden Karau] Instead of using a private inverse transform, add an invert function so we can use it in a pipeline
88779c1 [Holden Karau] fix long line
78b28c1 [Holden Karau] Finish reverse part and add a test :)
bb16a6a [Holden Karau] Some progress
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
optimization
Adds `alpha` (document-topic Dirichlet parameter) hyperparameter optimization to `OnlineLDAOptimizer` following Huang: Maximum Likelihood Estimation of Dirichlet Distribution Parameters. Also introduces a private `setSampleWithReplacement` to `OnlineLDAOptimizer` for unit testing purposes.
Author: Feynman Liang <fliang@databricks.com>
Closes #7836 from feynmanliang/SPARK-8936-alpha-optimize and squashes the following commits:
4bef484 [Feynman Liang] Documentation improvements
c3c6c1d [Feynman Liang] Fix docs
151e859 [Feynman Liang] Fix style
fa77518 [Feynman Liang] Hyperparameter optimization
|
|
|
|
|
|
|
|
|
|
|
|
| |
Make NaiveBayesModel support predicting class probabilities, inherit from ProbabilisticClassificationModel.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #7672 from yanboliang/spark-9308 and squashes the following commits:
25e224c [Yanbo Liang] raw2probabilityInPlace should operate in-place
3ee56d6 [Yanbo Liang] change predictRaw and raw2probabilityInPlace
c07e7a2 [Yanbo Liang] ml.NaiveBayesModel support predicting class probabilities
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Add topDocumentsPerTopic to DistributedLDAModel.
Add ScalaDoc and unit tests.
Author: Meihua Wu <meihuawu@umich.edu>
Closes #7769 from rotationsymmetry/SPARK-9246 and squashes the following commits:
1029e79c [Meihua Wu] clean up code comments
a023b82 [Meihua Wu] Update tests to use Long for doc index.
91e5998 [Meihua Wu] Use Long for doc index.
b9f70cf [Meihua Wu] Revise topDocumentsPerTopic
26ff3f6 [Meihua Wu] Add topDocumentsPerTopic, scala doc and unit tests
|
|
|
|
|
|
|
|
|
|
|
| |
jkbradley Exposes `bound` (variational log likelihood bound) through public API as `logLikelihood`. Also adds unit tests, some DRYing of `LDASuite`, and includes unit tests mentioned in #7760
Author: Feynman Liang <fliang@databricks.com>
Closes #7801 from feynmanliang/SPARK-9481-logLikelihood and squashes the following commits:
6d1b2c9 [Feynman Liang] Negate perplexity definition
5f62b20 [Feynman Liang] Add logLikelihood
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Decision tree support predict class probabilities.
Implement the prediction probabilities function referred the old DecisionTree API and the [sklean API](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/tree.py#L593).
I make the DecisionTreeClassificationModel inherit from ProbabilisticClassificationModel, make the predictRaw to return the raw counts vector and make raw2probabilityInPlace/predictProbability return the probabilities for each prediction.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #7694 from yanboliang/spark-6885 and squashes the following commits:
08d5b7f [Yanbo Liang] fix ImpurityStats null parameters and raw2probabilityInPlace sum = 0 issue
2174278 [Yanbo Liang] solve merge conflicts
7e90ba8 [Yanbo Liang] fix typos
33ae183 [Yanbo Liang] fix annotation
ff043d3 [Yanbo Liang] raw2probabilityInPlace should operate in-place
c32d6ce [Yanbo Liang] optimize calculateImpurityStats function again
6167fb0 [Yanbo Liang] optimize calculateImpurityStats function
fbbe2ec [Yanbo Liang] eliminate duplicated struct and code
beb1634 [Yanbo Liang] try to eliminate impurityStats for each LearningNode
99e8943 [Yanbo Liang] code optimization
5ec3323 [Yanbo Liang] implement InformationGainAndImpurityStats
227c91b [Yanbo Liang] refactor LearningNode to store ImpurityCalculator
d746ffc [Yanbo Liang] decision tree support predict class probabilities
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
jira: https://issues.apache.org/jira/browse/SPARK-9231
Helper method in DistributedLDAModel of this form:
```
/**
* For each document, return the top k weighted topics for that document.
* return RDD of (doc ID, topic indices, topic weights)
*/
def topTopicsPerDocument(k: Int): RDD[(Long, Array[Int], Array[Double])]
```
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #7785 from hhbyyh/topTopicsPerdoc and squashes the following commits:
30ad153 [Yuhao Yang] small fix
fd24580 [Yuhao Yang] add topTopics per document to DistributedLDAModel
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
This pull request contains the following feature for ML:
- Multilayer Perceptron classifier
This implementation is based on our initial pull request with bgreeven: https://github.com/apache/spark/pull/1290 and inspired by very insightful suggestions from mengxr and witgo (I would like to thank all other people from the mentioned thread for useful discussions). The original code was extensively tested and benchmarked. Since then, I've addressed two main requirements that prevented the code from merging into the main branch:
- Extensible interface, so it will be easy to implement new types of networks
- Main building blocks are traits `Layer` and `LayerModel`. They are used for constructing layers of ANN. New layers can be added by extending the `Layer` and `LayerModel` traits. These traits are private in this release in order to save path to improve them based on community feedback
- Back propagation is implemented in general form, so there is no need to change it (optimization algorithm) when new layers are implemented
- Speed and scalability: this implementation has to be comparable in terms of speed to the state of the art single node implementations.
- The developed benchmark for large ANN shows that the proposed code is on par with C++ CPU implementation and scales nicely with the number of workers. Details can be found here: https://github.com/avulanov/ann-benchmark
- DBN and RBM by witgo https://github.com/witgo/spark/tree/ann-interface-gemm-dbn
- Dropout https://github.com/avulanov/spark/tree/ann-interface-gemm
mengxr and dbtsai kindly agreed to perform code review.
Author: Alexander Ulanov <nashb@yandex.ru>
Author: Bert Greevenbosch <opensrc@bertgreevenbosch.nl>
Closes #7621 from avulanov/SPARK-2352-ann and squashes the following commits:
4806b6f [Alexander Ulanov] Addressing reviewers comments.
a7e7951 [Alexander Ulanov] Default blockSize: 100. Added documentation to blockSize parameter and DataStacker class
f69bb3d [Alexander Ulanov] Addressing reviewers comments.
374bea6 [Alexander Ulanov] Moving ANN to ML package. GradientDescent constructor is now spark private.
43b0ae2 [Alexander Ulanov] Addressing reviewers comments. Adding multiclass test.
9d18469 [Alexander Ulanov] Addressing reviewers comments: unnecessary copy of data in predict
35125ab [Alexander Ulanov] Style fix in tests
e191301 [Alexander Ulanov] Apache header
a226133 [Alexander Ulanov] Multilayer Perceptron regressor and classifier
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
support ml.NaiveBayes for Python
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #7568 from yanboliang/spark-9214 and squashes the following commits:
5ee3fd6 [Yanbo Liang] fix typos
3ecd046 [Yanbo Liang] fix typos
f9c94d1 [Yanbo Liang] change lambda_ to smoothing and fix other issues
180452a [Yanbo Liang] fix typos
7dda1f4 [Yanbo Liang] support ml.NaiveBayes for Python
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Multiclass Classification Evaluator for ML Pipelines. F1 score, precision, recall, weighted precision and weighted recall are supported as available metrics.
Author: Ram Sriharsha <rsriharsha@hw11853.local>
Closes #7475 from harsha2010/SPARK-7690 and squashes the following commits:
9bf4ec7 [Ram Sriharsha] fix indentation
3f09a85 [Ram Sriharsha] cleanup doc
16115ae [Ram Sriharsha] code review fixes
032d2a3 [Ram Sriharsha] fix test
eec9865 [Ram Sriharsha] Fix Python Indentation
1dbeffd [Ram Sriharsha] Merge branch 'master' into SPARK-7690
68cea85 [Ram Sriharsha] Merge branch 'master' into SPARK-7690
54c03de [Ram Sriharsha] [SPARK-7690][ml][WIP] Multiclass Evaluator for ML Pipeline
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Preview:
```
> summary(m)
features coefficients
1 (Intercept) 1.6765001
2 Sepal_Length 0.3498801
3 Species.versicolor -0.9833885
4 Species.virginica -1.0075104
```
Design doc from umbrella task: https://docs.google.com/document/d/10NZNSEurN2EdWM31uFYsgayIPfCFHiuIu3pCWrUmP_c/edit
cc mengxr
Author: Eric Liang <ekl@databricks.com>
Closes #7771 from ericl/summary and squashes the following commits:
ccd54c3 [Eric Liang] second pass
a5ca93b [Eric Liang] comments
2772111 [Eric Liang] clean up
70483ef [Eric Liang] fix test
7c247d4 [Eric Liang] Merge branch 'master' into summary
3c55024 [Eric Liang] working
8c539aa [Eric Liang] first pass
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Add checkpointing to GradientBoostedTrees, GBTClassifier, GBTRegressor
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #7804 from jkbradley/gbt-checkpoint3 and squashes the following commits:
3fbd7ba [Joseph K. Bradley] tiny fix
b3e160c [Joseph K. Bradley] unset checkpoint dir after test
9cc3a04 [Joseph K. Bradley] added checkpointing to GBTs
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Author: martinzapletal <zapletal-martin@email.cz>
Closes #7517 from zapletal-martin/SPARK-8671-isotonic-regression-api and squashes the following commits:
8c435c1 [martinzapletal] Review https://github.com/apache/spark/pull/7517 feedback update.
bebbb86 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-8671-isotonic-regression-api
b68efc0 [martinzapletal] Added tests for param validation.
07c12bd [martinzapletal] Comments and refactoring.
834fcf7 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-8671-isotonic-regression-api
b611fee [martinzapletal] SPARK-8671. Added first version of isotonic regression to pipeline API
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
build and other potential test failures in Streaming
See https://issues.apache.org/jira/browse/SPARK-9479 for the failure cause.
The PR includes the following changes:
1. Make ReceiverTrackerSuite create StreamingContext in the test body.
2. Fix places that don't stop StreamingContext. I verified no SparkContext was stopped in the shutdown hook locally after this fix.
3. Fix an issue that `ReceiverTracker.endpoint` may be null.
4. Make sure stopping SparkContext in non-main thread won't fail other tests.
Author: zsxwing <zsxwing@gmail.com>
Closes #7797 from zsxwing/fix-ReceiverTrackerSuite and squashes the following commits:
3a4bb98 [zsxwing] Fix another potential NPE
d7497df [zsxwing] Fix ReceiverTrackerSuite; make sure StreamingContext in tests is closed
|
|
|
|
|
|
|
|
|
|
|
|
| |
jkbradley Changes the current hacky string-comparison for vector compares.
Author: Feynman Liang <fliang@databricks.com>
Closes #7775 from feynmanliang/SPARK-9454-ldasuite-vector-compare and squashes the following commits:
bd91a82 [Feynman Liang] Remove println
905c76e [Feynman Liang] Fix string compare in distributed EM
2f24c13 [Feynman Liang] Improve LDASuite tests
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
jkbradley hhbyyh
Adds `topicDistributions` to LocalLDAModel. Please review after #7757 is merged.
Author: Feynman Liang <fliang@databricks.com>
Closes #7760 from feynmanliang/SPARK-5567-predict-in-LDA and squashes the following commits:
0ad1134 [Feynman Liang] Remove println
27b3877 [Feynman Liang] Code review fixes
6bfb87c [Feynman Liang] Remove extra newline
476f788 [Feynman Liang] Fix checks and doc for variationalInference
061780c [Feynman Liang] Code review cleanup
3be2947 [Feynman Liang] Rename topicDistribution -> topicDistributions
2a821a6 [Feynman Liang] Add predict methods to LocalLDAModel
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
declared number of elements less than array length
Check that SparseVector size is at least as big as the number of indices/values provided. And add tests for constructor checks.
CC MechCoder jkbradley -- I am not sure if a change needs to also happen in the Python API? I didn't see it had any similar checks to begin with, but I don't know it well.
Author: Sean Owen <sowen@cloudera.com>
Closes #7794 from srowen/SPARK-9277 and squashes the following commits:
e8dc31e [Sean Owen] Fix scalastyle
6ffe34a [Sean Owen] Check that SparseVector size is at least as big as the number of indices/values provided. And add tests for constructor checks.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Add unit tests for running LDA with empty documents.
Both EMLDAOptimizer and OnlineLDAOptimizer are tested.
feynmanliang
Author: Meihua Wu <meihuawu@umich.edu>
Closes #7620 from rotationsymmetry/SPARK-9225 and squashes the following commits:
3ed7c88 [Meihua Wu] Incorporate reviewer's further comments
f9432e8 [Meihua Wu] Incorporate reviewer's comments
8e1b9ec [Meihua Wu] Merge remote-tracking branch 'upstream/master' into SPARK-9225
ad55665 [Meihua Wu] Add unit tests for running LDA with empty documents
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
databases
Continuation of work by zhangjiajin
Closes #7412
Author: zhangjiajin <zhangjiajin@huawei.com>
Author: Feynman Liang <fliang@databricks.com>
Author: zhang jiajin <zhangjiajin@huawei.com>
Closes #7783 from feynmanliang/SPARK-8998-improve-distributed and squashes the following commits:
a61943d [Feynman Liang] Collect small patterns to local
4ddf479 [Feynman Liang] Parallelize freqItemCounts
ad23aa9 [zhang jiajin] Merge pull request #1 from feynmanliang/SPARK-8998-collectBeforeLocal
87fa021 [Feynman Liang] Improve extend prefix readability
c2caa5c [Feynman Liang] Readability improvements and comments
1235cfc [Feynman Liang] Use Iterable[Array[_]] over Array[Array[_]] for database
da0091b [Feynman Liang] Use lists for prefixes to reuse data
cb2a4fc [Feynman Liang] Inline code for readability
01c9ae9 [Feynman Liang] Add getters
6e149fa [Feynman Liang] Fix splitPrefixSuffixPairs
64271b3 [zhangjiajin] Modified codes according to comments.
d2250b7 [zhangjiajin] remove minPatternsBeforeLocalProcessing, add maxSuffixesBeforeLocalProcessing.
b07e20c [zhangjiajin] Merge branch 'master' of https://github.com/apache/spark into CollectEnoughPrefixes
095aa3a [zhangjiajin] Modified the code according to the review comments.
baa2885 [zhangjiajin] Modified the code according to the review comments.
6560c69 [zhangjiajin] Add feature: Collect enough frequent prefixes before projection in PrefixeSpan
a8fde87 [zhangjiajin] Merge branch 'master' of https://github.com/apache/spark
4dd1c8a [zhangjiajin] initialize file before rebase.
078d410 [zhangjiajin] fix a scala style error.
22b0ef4 [zhangjiajin] Add feature: Collect enough frequent prefixes before projection in PrefixSpan.
ca9c4c8 [zhangjiajin] Modified the code according to the review comments.
574e56c [zhangjiajin] Add new object LocalPrefixSpan, and do some optimization.
ba5df34 [zhangjiajin] Fix a Scala style error.
4c60fb3 [zhangjiajin] Fix some Scala style errors.
1dd33ad [zhangjiajin] Modified the code according to the review comments.
89bc368 [zhangjiajin] Fixed a Scala style error.
a2eb14c [zhang jiajin] Delete PrefixspanSuite.scala
951fd42 [zhang jiajin] Delete Prefixspan.scala
575995f [zhangjiajin] Modified the code according to the review comments.
91fd7e6 [zhangjiajin] Add new algorithm PrefixSpan and test file.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
PeriodicGraphCheckpointer was introduced for Latent Dirichlet Allocation (LDA), but it was meant to be generalized to work with Graphs, RDDs, and other data structures based on RDDs. This PR generalizes it.
For those who are not familiar with the periodic checkpointer, it tries to automatically handle persisting/unpersisting and checkpointing/removing checkpoint files in a lineage of RDD-based objects.
I need it generalized to use with GradientBoostedTrees [https://issues.apache.org/jira/browse/SPARK-6684]. It should be useful for other iterative algorithms as well.
Changes I made:
* Copied PeriodicGraphCheckpointer to PeriodicCheckpointer.
* Within PeriodicCheckpointer, I created abstract methods for the basic operations (checkpoint, persist, etc.).
* The subclasses for Graphs and RDDs implement those abstract methods.
* I copied the test suite for the graph checkpointer and made tiny modifications to make it work for RDDs.
To review this PR, I recommend doing 2 diffs:
(1) diff between the old PeriodicGraphCheckpointer.scala and the new PeriodicCheckpointer.scala
(2) diff between the 2 test suites
CCing andrewor14 in case there are relevant changes to checkpointing.
CCing feynmanliang in case you're interested in learning about checkpointing.
CCing mengxr for final OK.
Thanks all!
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #7728 from jkbradley/gbt-checkpoint and squashes the following commits:
d41902c [Joseph K. Bradley] Oops, forgot to update an extra time in the checkpointer tests, after the last commit. I'll fix that. I'll also make some of the checkpointer methods protected, which I should have done before.
32b23b8 [Joseph K. Bradley] fixed usage of checkpointer in lda
0b3dbc0 [Joseph K. Bradley] Changed checkpointer constructor not to take initial data.
568918c [Joseph K. Bradley] Generalized PeriodicGraphCheckpointer to PeriodicCheckpointer, with subclasses for RDDs and Graphs.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
jira: https://issues.apache.org/jira/browse/SPARK-7368
Add QR decomposition for RowMatrix.
I'm not sure what's the blueprint about the distributed Matrix from community and whether this will be a desirable feature , so I sent a prototype for discussion. I'll go on polish the code and provide ut and performance statistics if it's acceptable.
The implementation refers to the [paper: https://www.cs.purdue.edu/homes/dgleich/publications/Benson%202013%20-%20direct-tsqr.pdf]
Austin R. Benson, David F. Gleich, James Demmel. "Direct QR factorizations for tall-and-skinny matrices in MapReduce architectures", 2013 IEEE International Conference on Big Data, which is a stable algorithm with good scalability.
Currently I tried it on a 400000 * 500 rowMatrix (16 partitions) and it can bring down the computation time from 8.8 mins (using breeze.linalg.qr.reduced) to 2.6 mins on a 4 worker cluster. I think there will still be some room for performance improvement.
Any trial and suggestion is welcome.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #5909 from hhbyyh/qrDecomposition and squashes the following commits:
cec797b [Yuhao Yang] remove unnecessary qr
0fb1012 [Yuhao Yang] hierarchy R computing
3fbdb61 [Yuhao Yang] update qr to indirect and add ut
0d913d3 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into qrDecomposition
39213c3 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into qrDecomposition
c0fc0c7 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into qrDecomposition
39b0b22 [Yuhao Yang] initial draft for discussion
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
jkbradley MechCoder
Resolves blocking issue for SPARK-6793. Please review after #7705 is merged.
Author: Feynman Liang <fliang@databricks.com>
Closes #7757 from feynmanliang/SPARK-9940-localSaveLoad and squashes the following commits:
d0d8cf4 [Feynman Liang] Fix thisClassName
0f30109 [Feynman Liang] Fix tests after changing LDAModel public API
dc61981 [Feynman Liang] Add hyperparams to LocalLDAModel save/load
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Implement the classification trait for RandomForestClassifiers. The plan is to use this in the future to providing thresholding for RandomForestClassifiers (as well as other classifiers that implement that trait).
Author: Holden Karau <holden@pigscanfly.ca>
Closes #7432 from holdenk/SPARK-9016-make-random-forest-classifiers-implement-classification-trait and squashes the following commits:
bf22fa6 [Holden Karau] Add missing imports for testing suite
e948f0d [Holden Karau] Check the prediction generation from rawprediciton
25320c3 [Holden Karau] Don't supply numClasses when not needed, assert model classes are as expected
1a67e04 [Holden Karau] Use old decission tree stuff instead
673e0c3 [Holden Karau] Merge branch 'master' into SPARK-9016-make-random-forest-classifiers-implement-classification-trait
0d15b96 [Holden Karau] FIx typo
5eafad4 [Holden Karau] add a constructor for rootnode + num classes
fc6156f [Holden Karau] scala style fix
2597915 [Holden Karau] take num classes in constructor
3ccfe4a [Holden Karau] Merge in master, make pass numClasses through randomforest for training
222a10b [Holden Karau] Increase numtrees to 3 in the python test since before the two were equal and the argmax was selecting the last one
16aea1c [Holden Karau] Make tests match the new models
b454a02 [Holden Karau] Make the Tree classifiers extends the Classifier base class
77b4114 [Holden Karau] Import vectors lib
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Implements `logPerplexity` in `OnlineLDAOptimizer`. Also refactors inference code into companion object to enable future reuse (e.g. `predict` method).
Author: Feynman Liang <fliang@databricks.com>
Closes #7705 from feynmanliang/SPARK-6793-perplexity and squashes the following commits:
6da2c99 [Feynman Liang] Remove get* from LDAModel public API
8381da6 [Feynman Liang] Code review comments
17f7000 [Feynman Liang] Documentation typo fixes
2f452a4 [Feynman Liang] Remove auxillary DistributedLDAModel constructor
a275914 [Feynman Liang] Prevent empty counts calls to variationalInference
06d02d9 [Feynman Liang] Remove deprecated LocalLDAModel constructor
afecb46 [Feynman Liang] Fix regression bug in sstats accumulator
5a327a0 [Feynman Liang] Code review quick fixes
998c03e [Feynman Liang] Fix style
1cbb67d [Feynman Liang] Fix access modifier bug
4362daa [Feynman Liang] Organize imports
4f171f7 [Feynman Liang] Fix indendation
2f049ce [Feynman Liang] Fix failing save/load tests
7415e96 [Feynman Liang] Pick changes from big PR
11e7c33 [Feynman Liang] Merge remote-tracking branch 'apache/master' into SPARK-6793-perplexity
f8adc48 [Feynman Liang] Add logPerplexity, refactor variationalBound into a method
cd521d6 [Feynman Liang] Refactor methods into companion class
7f62a55 [Feynman Liang] --amend
c62cb1e [Feynman Liang] Outer product for stats, revert Range slicing
aead650 [Feynman Liang] Range slice, in-place update, reduce transposes
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Adds '.', '-', and intercept parsing to RFormula. Also splits RFormulaParser into a separate file.
Umbrella design doc here: https://docs.google.com/document/d/10NZNSEurN2EdWM31uFYsgayIPfCFHiuIu3pCWrUmP_c/edit?usp=sharing
mengxr
Author: Eric Liang <ekl@databricks.com>
Closes #7707 from ericl/string-features-2 and squashes the following commits:
8588625 [Eric Liang] exclude complex types for .
8106ffe [Eric Liang] comments
a9350bb [Eric Liang] s/var/val
9c50d4d [Eric Liang] Merge branch 'string-features' into string-features-2
581afb2 [Eric Liang] Merge branch 'master' into string-features
08ae539 [Eric Liang] Merge branch 'string-features' into string-features-2
f99131a [Eric Liang] comments
cecec43 [Eric Liang] Merge branch 'string-features' into string-features-2
0bf3c26 [Eric Liang] update docs
4592df2 [Eric Liang] intercept supports
7412a2e [Eric Liang] Fri Jul 24 14:56:51 PDT 2015
3cf848e [Eric Liang] fix the parser
0556c2b [Eric Liang] Merge branch 'string-features' into string-features-2
c302a2c [Eric Liang] fix tests
9d1ac82 [Eric Liang] Merge remote-tracking branch 'upstream/master' into string-features
e713da3 [Eric Liang] comments
cd231a9 [Eric Liang] Wed Jul 22 17:18:44 PDT 2015
4d79193 [Eric Liang] revert to seq + distinct
169a085 [Eric Liang] tweak functional test
a230a47 [Eric Liang] Merge branch 'master' into string-features
72bd6f3 [Eric Liang] fix merge
d841cec [Eric Liang] Merge branch 'master' into string-features
5b2c4a2 [Eric Liang] Mon Jul 20 18:45:33 PDT 2015
b01c7c5 [Eric Liang] add test
8a637db [Eric Liang] encoder wip
a1d03f4 [Eric Liang] refactor into estimator
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
This adds StringType feature support via OneHotEncoder. As part of this task it was necessary to change RFormula to an Estimator, so that factor levels could be determined from the training dataset.
Not sure if I am using uids correctly here, would be good to get reviewer help on that.
cc mengxr
Umbrella design doc: https://docs.google.com/document/d/10NZNSEurN2EdWM31uFYsgayIPfCFHiuIu3pCWrUmP_c/edit#
Author: Eric Liang <ekl@databricks.com>
Closes #7574 from ericl/string-features and squashes the following commits:
f99131a [Eric Liang] comments
0bf3c26 [Eric Liang] update docs
c302a2c [Eric Liang] fix tests
9d1ac82 [Eric Liang] Merge remote-tracking branch 'upstream/master' into string-features
e713da3 [Eric Liang] comments
4d79193 [Eric Liang] revert to seq + distinct
169a085 [Eric Liang] tweak functional test
a230a47 [Eric Liang] Merge branch 'master' into string-features
72bd6f3 [Eric Liang] fix merge
d841cec [Eric Liang] Merge branch 'master' into string-features
5b2c4a2 [Eric Liang] Mon Jul 20 18:45:33 PDT 2015
b01c7c5 [Eric Liang] add test
8a637db [Eric Liang] encoder wip
a1d03f4 [Eric Liang] refactor into estimator
|
|
|
|
|
|
|
|
|
|
|
|
| |
jira: https://issues.apache.org/jira/browse/SPARK-9337
Word2Vec should throw exception when vocabulary is empty
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #7660 from hhbyyh/ut4Word2vec and squashes the following commits:
17a18cb [Yuhao Yang] add ut for word2vec
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Word2Vec used to convert from an Array[Float] representation to a Map[String, Array[Float]] and then back to an Array[Float] through Word2VecModel.
This prevents this conversion while still supporting the older method of supplying a Map.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes #5748 from MechCoder/spark-7045 and squashes the following commits:
e308913 [MechCoder] move docs
5703116 [MechCoder] minor
fa04313 [MechCoder] style fixes
b1d61c4 [MechCoder] better errors and tests
3b32c8c [MechCoder] [SPARK-7045] Avoid intermediate representation when creating model
|
|
|
|
|
|
|
|
|
|
|
|
| |
DistributedLDAModel private[clustering]
This makes it easier to test all the class variables of the DistributedLDAmodel.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes #7573 from MechCoder/lda_test and squashes the following commits:
2f1a293 [MechCoder] [SPARK-9222] [MLlib] Make class instantiation variables in DistributedLDAModel private[clustering]
|