Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/4610#discussion_r2537
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala ---
@@ -66,9 +66,17 @@ private[sql] class DefaultSource
mode
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5038#issuecomment-82787376
@srowen , sorry for the misunderstand. I have change to use string
interpolation and delete ```toDebugString``` which may be useless.
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4610#issuecomment-83545467
@yhuai Thank you for your comments on this PR
@liancheng If this LGTM, can I open another PR for ```ParquetRelation2```
and work on it?
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5016#issuecomment-83940710
@mengxr Thank you for your comments.
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5106
[SPARK-6096] [MLLIB] Support model save/load in Python's Naive Bayes
Model save/load in Python's Naive Bayes which reuse the Scala save/load
implementation.
You can merge this pull request
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5107
[SPARK-5821] [SQL] ParquetRelation2 CTAS should check if delete is
successful
Do the same check as #4610 for ParquetRelation2.
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4997#issuecomment-84051013
@jkbradley @mengxr Can you review this patch?
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5106#issuecomment-84254673
@mengxr Sorry for miss check, I will close this PR, thank you.
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Github user yanboliang closed the pull request at:
https://github.com/apache/spark/pull/5106
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4610#issuecomment-84065407
@liancheng Please review my fix for ParquetRelation2 in #5107
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5038
[SPARK-6291] [MLLIB] GLM toString toDebugString
GLM toString prints out intercept, numFeatures.
For LogisticRegression and SVM model, toString also prints out numClasses,
threshold.
GLM
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4911#issuecomment-77854374
@mengxr Yes, it make sense, I will try to implement the save/load operation
in Python which do the same thing as in Scala.
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/4997
[SPARK-6256] [MLlib] MLlib Python API parity check for regression
MLlib Python API parity check for Regression, major disparities list
following:
LinearRegressionWithSGD
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4911#issuecomment-77572142
@mengxr Yes, it make sense. After look through the code, I found we have
two alternatives:
1, Implement a new PythonMLLibAPI looks like this
def
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5016#issuecomment-79633944
retest, please.
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Github user yanboliang closed the pull request at:
https://github.com/apache/spark/pull/4911
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5016
Support model save/load in Python's linear models
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4911#issuecomment-79110275
Sorry I closed this PR accidentally, I pull another request #5016 for this
issue.
I have implement save/load operation in Python for classification model
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/4997#discussion_r27030181
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala ---
@@ -111,9 +111,11 @@ private[python] class PythonMLLibAPI
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5167
LogisticRegressionWithLBFGS.run(input, initialWeights) should initialize
numFeatures
LogisticRegressionWithLBFGS.run(input, initialWeights) should initialize
numFeatures
You can merge
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5137#issuecomment-85571917
@jkbradley @mengxr
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5270
[SPARK-5990] [MLLIB] Model import/export for IsotonicRegression
Model import/export for IsotonicRegression
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27545988
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -145,13 +135,20 @@ class LogisticRegressionModel
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27500087
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -106,7 +118,6 @@ class LogisticRegressionModel
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27499535
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -145,13 +135,20 @@ class LogisticRegressionModel
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27497189
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -106,7 +118,6 @@ class LogisticRegressionModel
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27499263
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -145,13 +135,20 @@ class LogisticRegressionModel
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27498701
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -145,13 +135,20 @@ class LogisticRegressionModel
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5249#discussion_r27498752
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -145,13 +135,20 @@ class LogisticRegressionModel
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5249#issuecomment-88176235
@srowen Thank you for your comments, I have updated the commits.
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5137#issuecomment-88176441
@jkbradley Thank you for your comments.
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5249#issuecomment-87369690
retest please
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5249
[SPARK-6580] [MLLIB] Optimize LogisticRegressionModel.predictPoint
https://issues.apache.org/jira/browse/SPARK-6580
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5137
[SPARK-6255] [MLLIB] Python API parity check for classification
Python API parity check for classification
Support multiclass classification in pyspark
You can merge this pull request
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5137#issuecomment-85059666
This PR is work in progress, I still need to make
LogisticRegressionModel.predict can handle multiclass classification.
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/4831
correct LogisticRegressionWithLBFGS regType parameter for pyspark
Currently LogisticRegressionWithLBFGS in
python/pyspark/mllib/classification.py will invoke callMLlibFunc with a wrong
regType
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/4831#discussion_r25582380
--- Diff: python/pyspark/mllib/classification.py ---
@@ -207,7 +207,7 @@ def train(cls, data, iterations=100,
initialWeights=None, regParam=0.01, regType
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/4911
[SPARK-6095] [MLLIB] Support model save/load in Python's linear models
Linear models can be stored in Python which is different from other models
currently.
So we leverage pickle
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4707#issuecomment-75437798
test please
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4707#issuecomment-75536583
retest please
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/4707#issuecomment-75439264
retest please
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/4707
[SPARK-5926] [SQL] make DataFrame.explain leverage queryExecution.logical
DataFrame.explain return wrong result when the query is DDL command.
For example, the following two queries
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/4707#discussion_r25091776
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala ---
@@ -123,7 +123,7 @@ class DataFrame protected[sql
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5213
[SPARK-6264] [MLLIB] Support FPGrowth algorithm in Python API
Support FPGrowth algorithm in Python API
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5614
[SPARK-6827] [mllib] Wrap FPGrowthModel.freqItemsets and make it consistent
with Java API
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Github user yanboliang closed the pull request at:
https://github.com/apache/spark/pull/4527
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5614#issuecomment-95011704
@mengxr Thank you for your comments and help, I have merged your PR to this
PR.
I will investigate the pickle/unpickle problems and file another PR to
resolve
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5890
[SPARK-6267] [MLLIB] Python API for IsotonicRegression
https://issues.apache.org/jira/browse/SPARK-6267
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5941
[SPARK-6093] [MLLIB] Add RegressionMetrics in PySpark/MLlib
https://issues.apache.org/jira/browse/SPARK-6093
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/5939
[SPARK-5913] [MLLIB] Python API for ChiSqSelector
https://issues.apache.org/jira/browse/SPARK-5913
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5941#issuecomment-100102143
@mengxr , OK, I will take them.
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5939#issuecomment-100115666
@jkbradley , I think the Python docs for ChiSqSelector and
ChiSqSelectorModel have reached parity with Scala ones. Please correct me is I
misunderstand.
Yes, I
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/5941#discussion_r29867547
--- Diff: python/pyspark/mllib/evaluation.py ---
@@ -67,6 +67,73 @@ def unpersist(self):
self.call(unpersist)
+class
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/5939#issuecomment-99925969
@mengxr , @jkbradley
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6011
[SPARK-6091] [MLLIB] Add MulticlassMetrics in PySpark/MLlib
https://issues.apache.org/jira/browse/SPARK-6091
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6044#issuecomment-100792972
It looks like py4j can not recognize [T: ClassTag] for RankingMetrics.
If I removed [T: ClassTag] and specify the type (for example: Int) of
RankingMetrics, py4j
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6044#issuecomment-100752796
Jenkins, retest this please
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6044#issuecomment-100907856
Jenkins, retest this please
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6044
[SPARK-6092] [MLLIB] Add RankingMetrics in PySpark/MLlib
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6011#issuecomment-100512819
Retest please
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6087#discussion_r30215924
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala ---
@@ -345,28 +345,39 @@ private[python] class PythonMLLibAPI
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6087#discussion_r3021
--- Diff: python/pyspark/mllib/clustering.py ---
@@ -166,12 +166,39 @@ class GaussianMixtureModel(object):
True
labels[3]==labels[4
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6087#issuecomment-101624047
@FlytxtRnD , at Scala we use three parameters separately to construct
```GaussianMixtureModel```. So if we pass a single compacting list, we need to
unfold
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6087
[SPARK-6258] [MLLIB] GaussianMixture Python API parity check
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6087#issuecomment-101942746
gassian[i]
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6087#issuecomment-101948297
weightsi
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6087#issuecomment-101949379
gaussians[i]()
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6087#issuecomment-101949093
gaussians[i]
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6087#discussion_r30382722
--- Diff: python/pyspark/mllib/clustering.py ---
@@ -166,12 +168,38 @@ class GaussianMixtureModel(object):
True
labels[3]==labels[4
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6276
[SPARK-6094] [MLlib] Add MultilabelMetrics in PySpark/MLlib
Add MultilabelMetrics in PySpark/MLlib
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$ git pull https
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6315
[SPARK-7604] [MLlib] Python API for PCA and PCAModel
Python API for PCA and PCAModel
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$ git pull https://github.com
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/7011
[Minor] [MLLib] rename some functions of PythonMLLibAPI
Keep the same naming conventions for PythonMLLibAPI.
Only the following three function is different from others
```scala
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6992#issuecomment-115470960
@jkbradley @mengxr
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6991
[SPARK-5962] [MLlib] Python support for Power Iteration Clustering
Python support for Power Iteration Clustering
https://issues.apache.org/jira/browse/SPARK-5962
You can merge this pull
Github user yanboliang closed the pull request at:
https://github.com/apache/spark/pull/6991
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6992
[SPARK-5962] [MLlib] Python support for Power Iteration Clustering
Python support for Power Iteration Clustering
https://issues.apache.org/jira/browse/SPARK-5962
You can merge this pull
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6856#issuecomment-114429515
@jkbradley, ChiSqSelectorModel is not inheriting correctly and I change it
to the original style.
I have checked the merge issue and it can be merged cleanly if I
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6315#issuecomment-112646149
@jkbradley @mengxr
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6856#discussion_r32611917
--- Diff: python/pyspark/mllib/feature.py ---
@@ -123,20 +132,6 @@ class StandardScalerModel(JavaVectorTransformer):
Represents
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6856
[MLlib] [SPARK-7667] MLlib Python API consistency check
MLlib Python API consistency check
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6856#discussion_r32611974
--- Diff: python/pyspark/mllib/feature.py ---
@@ -205,14 +200,6 @@ class ChiSqSelectorModel(JavaVectorTransformer):
Represents a Chi Squared
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6460#issuecomment-112258204
retest
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6460#issuecomment-107009193
The length of docstring line for PEP8 standard is 72, so truncate too long
line.
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6461#discussion_r31378624
--- Diff: python/pyspark/mllib/evaluation.py ---
@@ -27,6 +27,8 @@ class BinaryClassificationMetrics(JavaModelWrapper):
Evaluator
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6461
[SPARK-7918] [MLlib] MLlib Python doc parity check for evaluation and
feature
Check then make the MLlib Python evaluation and feature doc to be as
complete as the Scala doc.
You can merge
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/6460
[SPARK-7916] [MLlib] [Doc] MLlib Python doc parity check for classification
and regression
Check then make the MLlib Python classification and regression doc to be as
complete as the Scala doc
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/7155
[SPARK-8758] [MLlib] Add Python user guide for PowerIterationClustering
Add Python user guide for PowerIterationClustering
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7177#discussion_r33747859
--- Diff: python/pyspark/mllib/clustering.py ---
@@ -282,18 +282,30 @@ class PowerIterationClusteringModel(JavaModelWrapper,
JavaSaveable, JavaLoader
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/7177
[SPARK-8765] [MLlib] Fix PySpark PowerIterationClustering test issue
PySpark PowerIterationClustering test failure due to bad
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/7164#issuecomment-117900730
@mengxr @jkbradley I have found the test failure caused by the small
dataset. If the dataset is small, PowerIterationClustering will behavior
indeterministic. I have
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/7177#issuecomment-118370370
@mengxr @jkbradley Yes, the cluster assignments is deterministic subject
to numerical difference. The current tests is deterministic right now just like
the test
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7184#discussion_r33868622
--- Diff: mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
---
@@ -0,0 +1,114 @@
+/*
+ * Licensed to the Apache Software
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/7184
[SPARK-8788] [ML] Add Java unit test for PCA transformer
Add Java unit test for PCA transformer
You can merge this pull request into a Git repository by running:
$ git pull https
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/7190
[SPARK-8792] [ML] Add Python API for PCA transformer
Add Python API for PCA transformer
You can merge this pull request into a Git repository by running:
$ git pull https://github.com
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6992#discussion_r33420166
--- Diff: python/pyspark/mllib/clustering.py ---
@@ -466,7 +557,8 @@ def predictOnValues(self, dstream):
def _test():
import doctest
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/7065
[SPARK-8664] [ML] Add PCA transformer
Add PCA transformer for ML pipeline
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yanboliang/spark
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6856#issuecomment-116222651
@jkbradley
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7065#discussion_r33420498
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala ---
@@ -68,7 +68,7 @@ class PCA(val k: Int) {
* @param k number of principal
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/6315#issuecomment-105149865
@mengxr @jkbradley
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7838#discussion_r36054229
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
---
@@ -30,7 +30,7 @@ import
org.apache.spark.mllib.tree.model
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