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zhengruifeng commented on SPARK-7008:
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thanks for this information!
An Implement of
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zhengruifeng updated SPARK-7008:
Summary: An implementation of Factorization Machine (LibFM) (was: An
Implement of Factorization
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zhengruifeng updated SPARK-7008:
Description:
An implement of Factorization Machines based on Scala and Spark MLlib.
Factorization
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zhengruifeng updated SPARK-7008:
Description:
An implementation of Factorization Machines based on Scala and Spark MLlib.
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zhengruifeng updated SPARK-7008:
Labels: features patch (was: features)
Implement of Factorization Machine (LibFM)
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zhengruifeng updated SPARK-7008:
Affects Version/s: 1.3.2
1.3.1
Implement of Factorization Machine (LibFM)
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zhengruifeng updated SPARK-7008:
Target Version/s: 1.3.0, 1.3.1, 1.3.2 (was: 1.3.0)
Implement of Factorization Machine (LibFM)
zhengruifeng created SPARK-7008:
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Summary: Implement of Factorization Machine (LibFM)
Key: SPARK-7008
URL: https://issues.apache.org/jira/browse/SPARK-7008
Project: Spark
Issue Type: New
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zhengruifeng commented on SPARK-7008:
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I had not considered of the size of model,
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zhengruifeng updated SPARK-7008:
Description:
An implementation of Factorization Machines based on Scala and Spark MLlib.
FM is a
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zhengruifeng edited comment on SPARK-7008 at 4/25/15 12:46 AM:
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zhengruifeng edited comment on SPARK-7008 at 4/25/15 12:44 AM:
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zhengruifeng commented on SPARK-7008:
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The convergence curves of Binary Classification
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zhengruifeng updated SPARK-7008:
Attachment: FM_CR.xlsx
An implementation of Factorization Machine (LibFM)
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zhengruifeng commented on SPARK-7008:
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AdaGrad works pretty well in practice, but I
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zhengruifeng closed SPARK-7008.
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Resolution: Fixed
An implementation of Factorization Machine (LibFM)
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zhengruifeng commented on SPARK-11585:
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I have implemented it based on Apriori's Rule-Generation
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zhengruifeng edited comment on SPARK-11585 at 11/9/15 8:11 AM:
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I have
zhengruifeng created SPARK-11585:
Summary: AssociationRules should generates all association rules
with consequents of arbitrary length
Key: SPARK-11585
URL: https://issues.apache.org/jira/browse/SPARK-11585
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zhengruifeng updated SPARK-11585:
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Attachment: rule-generation.pdf
Apriori's Rule Generation Algorithm
> AssociationRules should
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zhengruifeng commented on SPARK-7008:
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Yes, LBFGS provide a faster convergence rate.
zhengruifeng created SPARK-15770:
Summary: 'Experimental' annotation audit
Key: SPARK-15770
URL: https://issues.apache.org/jira/browse/SPARK-15770
Project: Spark
Issue Type: Improvement
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zhengruifeng updated SPARK-15770:
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Description:
1, remove comments {{:: Experimental ::}} for non-experimental API
2, add comments
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zhengruifeng updated SPARK-15770:
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Description:
1, remove comments {{:: Experimental ::}} for non-experimental API
2, add comments
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zhengruifeng updated SPARK-15770:
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Description:
1, remove comments {{:: Experimental ::}} for non-experimental API
2, add comments
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zhengruifeng updated SPARK-15770:
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Summary: annotation audit for Experimental and DeveloperApi (was:
'Experimental' annotation
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zhengruifeng edited comment on SPARK-15823 at 6/9/16 10:20 AM:
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zhengruifeng commented on SPARK-15823:
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{MulticlassMetrics.confusionMatrix} may need {@property}
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zhengruifeng updated SPARK-15823:
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Comment: was deleted
(was: {MulticlassMetrics.confusionMatrix} may need {@property} too, but I
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zhengruifeng commented on SPARK-15823:
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{MulticlassMetrics.confusionMatrix} may need {@property}
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zhengruifeng updated SPARK-15823:
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Summary: Add @property for 'accuracy' in MulticlassMetrics (was: Add
@property for 'property'
zhengruifeng created SPARK-15823:
Summary: Add @property for 'property' in MulticlassMetrics
Key: SPARK-15823
URL: https://issues.apache.org/jira/browse/SPARK-15823
Project: Spark
Issue
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zhengruifeng commented on SPARK-15617:
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I can work on this
> Clarify that fMeasure in
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zhengruifeng commented on SPARK-15617:
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zhengruifeng commented on SPARK-15581:
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In regard to gbt, xgboost4j may be involved
> MLlib 2.1
zhengruifeng created SPARK-15939:
Summary: Clarify ml.linalg usage
Key: SPARK-15939
URL: https://issues.apache.org/jira/browse/SPARK-15939
Project: Spark
Issue Type: Improvement
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zhengruifeng updated SPARK-15939:
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Description:
1, update comments in {{pyspark.ml}} that it use {{ml.linalg}} not
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zhengruifeng updated SPARK-15939:
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Description:
1, update comments in {{pyspark.ml}} that it use {ml.linalg} not {mllib.linalg}
2,
zhengruifeng created SPARK-15650:
Summary: Add correctness test for MulticlassClassification
Key: SPARK-15650
URL: https://issues.apache.org/jira/browse/SPARK-15650
Project: Spark
Issue
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zhengruifeng commented on SPARK-15614:
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Agreed.
What about setting the default value of
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zhengruifeng updated SPARK-15650:
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Summary: Add correctness test for MulticlassClassificationEvaluator (was:
Add correctness test
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zhengruifeng closed SPARK-15291.
Resolution: Won't Fix
> Remove redundant codes in SVD++
> ---
>
>
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zhengruifeng closed SPARK-15607.
Resolution: Won't Fix
> Remove redundant toArray in ml.linalg
>
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zhengruifeng updated SPARK-15610:
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Summary: update error message for k in pca (was: PCA should not support k
== numFeatures)
>
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zhengruifeng updated SPARK-15610:
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Priority: Minor (was: Major)
> PCA should not support k == numFeatures
>
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zhengruifeng updated SPARK-15610:
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Description: error message for {{k}} should match the bound (was: Vector
size must be greater
zhengruifeng created SPARK-15607:
Summary: Remove redundant toArray in ml.linalg
Key: SPARK-15607
URL: https://issues.apache.org/jira/browse/SPARK-15607
Project: Spark
Issue Type:
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zhengruifeng updated SPARK-15614:
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Priority: Minor (was: Major)
> ml.feature should support default value of input column
>
zhengruifeng created SPARK-15614:
Summary: ml.feature should support default value of input column
Key: SPARK-15614
URL: https://issues.apache.org/jira/browse/SPARK-15614
Project: Spark
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zhengruifeng commented on SPARK-15614:
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[~josephkb] [~mengxr] [~yanboliang] any thoughts?
>
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zhengruifeng edited comment on SPARK-15614 at 5/27/16 11:54 AM:
zhengruifeng created SPARK-15610:
Summary: PCA should not support k == numFeatures
Key: SPARK-15610
URL: https://issues.apache.org/jira/browse/SPARK-15610
Project: Spark
Issue Type: Bug
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zhengruifeng commented on SPARK-15617:
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Agreed.
In {{MulticlassClassificationEvaluator}}, I will
zhengruifeng created SPARK-13435:
Summary: Add Weighted Cohen's kappa to MulticlassMetrics
Key: SPARK-13435
URL: https://issues.apache.org/jira/browse/SPARK-13435
Project: Spark
Issue Type:
zhengruifeng created SPARK-13506:
Summary: Fix the wrong parameter in R code comment in
AssociationRulesSuite
Key: SPARK-13506
URL: https://issues.apache.org/jira/browse/SPARK-13506
Project: Spark
zhengruifeng created SPARK-13538:
Summary: Add GaussianMixture to ML
Key: SPARK-13538
URL: https://issues.apache.org/jira/browse/SPARK-13538
Project: Spark
Issue Type: Improvement
zhengruifeng created SPARK-13550:
Summary: Add java example for ml.clustering.BisectingKMeans
Key: SPARK-13550
URL: https://issues.apache.org/jira/browse/SPARK-13550
Project: Spark
Issue
zhengruifeng created SPARK-13551:
Summary: Fix fix wrong comment and remove meanless lines in
mllib.JavaBisectingKMeansExample
Key: SPARK-13551
URL: https://issues.apache.org/jira/browse/SPARK-13551
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zhengruifeng commented on SPARK-13435:
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I dont think so.
Recently, many Competitions use quadratic
zhengruifeng created SPARK-13385:
Summary: Enable AssociationRules to generate consequents with
user-defined lengths
Key: SPARK-13385
URL: https://issues.apache.org/jira/browse/SPARK-13385
Project:
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zhengruifeng updated SPARK-13385:
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Attachment: rule-generation.pdf
rule-generation algorithm
> Enable AssociationRules to generate
zhengruifeng created SPARK-13386:
Summary: ConnectedComponents should support maxIteration option
Key: SPARK-13386
URL: https://issues.apache.org/jira/browse/SPARK-13386
Project: Spark
Issue
zhengruifeng created SPARK-13416:
Summary: Add positive check for option 'numIter' in
StronglyConnectedComponents
Key: SPARK-13416
URL: https://issues.apache.org/jira/browse/SPARK-13416
Project:
zhengruifeng created SPARK-13814:
Summary: Delete unnecessary imports in python examples files
Key: SPARK-13814
URL: https://issues.apache.org/jira/browse/SPARK-13814
Project: Spark
Issue
zhengruifeng created SPARK-13816:
Summary: Add parameter checks for algorithms in Graphx
Key: SPARK-13816
URL: https://issues.apache.org/jira/browse/SPARK-13816
Project: Spark
Issue Type:
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zhengruifeng commented on SPARK-14005:
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I think easiness to implement should not be the reason to
zhengruifeng created SPARK-13970:
Summary: Add Non-Negative Matrix Factorization to MLlib
Key: SPARK-13970
URL: https://issues.apache.org/jira/browse/SPARK-13970
Project: Spark
Issue Type:
zhengruifeng created SPARK-14022:
Summary: What about adding RandomProjection to ML/MLLIB as a new
dimensionality reduction algorithm?
Key: SPARK-14022
URL: https://issues.apache.org/jira/browse/SPARK-14022
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zhengruifeng updated SPARK-13712:
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Comment: was deleted
(was: OK, I have closed the PR.
I had also planned to implement ECC after
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zhengruifeng commented on SPARK-13712:
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OK, I have closed the PR.
I had also planned to implement
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zhengruifeng commented on SPARK-13712:
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OK, I have closed the PR.
I had also planned to implement
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zhengruifeng commented on SPARK-14516:
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ok, I will work on clarify this API.
> Clustering evaluator
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zhengruifeng edited comment on SPARK-14516 at 4/13/16 12:22 PM:
ok, I
zhengruifeng created SPARK-14510:
Summary: Add args-checking for LDA and StreamingKMeans
Key: SPARK-14510
URL: https://issues.apache.org/jira/browse/SPARK-14510
Project: Spark
Issue Type:
zhengruifeng created SPARK-14509:
Summary: Add python CountVectorizerExample
Key: SPARK-14509
URL: https://issues.apache.org/jira/browse/SPARK-14509
Project: Spark
Issue Type: Improvement
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zhengruifeng updated SPARK-14022:
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Issue Type: Brainstorming (was: Question)
> What about adding RandomProjection to ML/MLLIB as a
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zhengruifeng reopened SPARK-14022:
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There may need some discuss on whether to add RandomProjection or Not.
> What about adding
zhengruifeng created SPARK-14514:
Summary: Add python example for VectorSlicer
Key: SPARK-14514
URL: https://issues.apache.org/jira/browse/SPARK-14514
Project: Spark
Issue Type: Improvement
zhengruifeng created SPARK-14515:
Summary: Add python example for ChiSqSelector
Key: SPARK-14515
URL: https://issues.apache.org/jira/browse/SPARK-14515
Project: Spark
Issue Type: Improvement
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zhengruifeng updated SPARK-14514:
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Component/s: Documentation
> Add python example for VectorSlicer
>
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zhengruifeng commented on SPARK-14022:
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Ok, I change the Type from Question to Brainstroming.
I
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zhengruifeng updated SPARK-13385:
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Priority: Major (was: Minor)
> Enable AssociationRules to generate consequents with
zhengruifeng created SPARK-14512:
Summary: Add python example for QuantileDiscretizer
Key: SPARK-14512
URL: https://issues.apache.org/jira/browse/SPARK-14512
Project: Spark
Issue Type:
zhengruifeng created SPARK-14516:
Summary: What about adding general clustering metrics?
Key: SPARK-14516
URL: https://issues.apache.org/jira/browse/SPARK-14516
Project: Spark
Issue Type:
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zhengruifeng commented on SPARK-14022:
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cc [~yanboliang] [~mengxr] [~josephkb]
> What about adding
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zhengruifeng commented on SPARK-14516:
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cc [~mengxr] [~josephkb] [~yanboliang]
> What about adding
zhengruifeng created SPARK-14027:
Summary: Add parameter check to GradientDescent
Key: SPARK-14027
URL: https://issues.apache.org/jira/browse/SPARK-14027
Project: Spark
Issue Type:
zhengruifeng created SPARK-14030:
Summary: Add parameter check to LBFGS
Key: SPARK-14030
URL: https://issues.apache.org/jira/browse/SPARK-14030
Project: Spark
Issue Type: Improvement
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zhengruifeng commented on SPARK-14005:
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ok, plz close this jira.
> Make RDD more compatible with
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zhengruifeng commented on SPARK-14174:
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There is another sklean example for MiniBatch KMeans:
zhengruifeng created SPARK-14174:
Summary: Accelerate KMeans via Mini-Batch EM
Key: SPARK-14174
URL: https://issues.apache.org/jira/browse/SPARK-14174
Project: Spark
Issue Type: Improvement
zhengruifeng created SPARK-14005:
Summary: Make RDD more compatible with Scala's collection
Key: SPARK-14005
URL: https://issues.apache.org/jira/browse/SPARK-14005
Project: Spark
Issue
zhengruifeng created SPARK-13677:
Summary: Support Tree-Based Feature Transformation for mllib
Key: SPARK-13677
URL: https://issues.apache.org/jira/browse/SPARK-13677
Project: Spark
Issue
zhengruifeng created SPARK-13672:
Summary: Add python examples of BisectingKMeans in ML and MLLIB
Key: SPARK-13672
URL: https://issues.apache.org/jira/browse/SPARK-13672
Project: Spark
Issue
zhengruifeng created SPARK-13714:
Summary: Another ConnectedComponents based on Max-Degree
Propagation
Key: SPARK-13714
URL: https://issues.apache.org/jira/browse/SPARK-13714
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-13714?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zhengruifeng updated SPARK-13714:
-
Description:
Current ConnectedComponents algorithm was based on Min-VertexId Propagation,
which
zhengruifeng created SPARK-13712:
Summary: Add OneVsOne to ML
Key: SPARK-13712
URL: https://issues.apache.org/jira/browse/SPARK-13712
Project: Spark
Issue Type: New Feature
zhengruifeng created SPARK-14352:
Summary: approxQuantile should support multi columns
Key: SPARK-14352
URL: https://issues.apache.org/jira/browse/SPARK-14352
Project: Spark
Issue Type:
zhengruifeng created SPARK-14272:
Summary: Evaluate GaussianMixtureModel with LogLooklihood
Key: SPARK-14272
URL: https://issues.apache.org/jira/browse/SPARK-14272
Project: Spark
Issue Type:
zhengruifeng created SPARK-14339:
Summary: Add python examples for DCT,MinMaxScaler,MaxAbsScaler
Key: SPARK-14339
URL: https://issues.apache.org/jira/browse/SPARK-14339
Project: Spark
Issue
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