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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2013) Create generalized linear model framework
Date Tue, 03 Oct 2017 04:00:02 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2013?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16189241#comment-16189241
] 

ASF GitHub Bot commented on FLINK-2013:
---------------------------------------

Github user bowenli86 commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3756#discussion_r142307430
  
    --- Diff: flink-libraries/flink-ml/src/test/scala/org/apache/flink/ml/regression/MultipleLinearRegressionITSuite.scala
---
    @@ -75,15 +75,16 @@ class MultipleLinearRegressionITSuite
     
         val parameters = ParameterMap()
     
    -    parameters.add(MultipleLinearRegression.Stepsize, 2.0)
    -    parameters.add(MultipleLinearRegression.Iterations, 10)
    -    parameters.add(MultipleLinearRegression.ConvergenceThreshold, 0.001)
    +    parameters.add(WithIterativeSolver.Stepsize, 2.0)
    +    parameters.add(WithIterativeSolver.Iterations, 10)
    +    parameters.add(WithIterativeSolver.ConvergenceThreshold, 0.001)
     
         mlr.fit(sparseInputDS, parameters)
     
         val weightList = mlr.weightsOption.get.collect()
     
         val WeightVector(weights, intercept) = weightList.head
    +    println(weightList)
    --- End diff --
    
    remove this?


> Create generalized linear model framework
> -----------------------------------------
>
>                 Key: FLINK-2013
>                 URL: https://issues.apache.org/jira/browse/FLINK-2013
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Theodore Vasiloudis
>            Assignee: Theodore Vasiloudis
>              Labels: ML
>
> [Generalized linear models|http://en.wikipedia.org/wiki/Generalized_linear_model] (GLMs)
provide an abstraction for many learning models that can be used for regression and classification
tasks.
> Some example GLMs are linear regression, logistic regression, LASSO and ridge regression.
> The goal for this JIRA is to provide interfaces for the set of common properties and
functions these models share. 
> In order to achieve that, a design pattern similar to the one that [sklearn|http://scikit-learn.org/stable/modules/linear_model.html]
and [MLlib|http://spark.apache.org/docs/1.3.0/mllib-linear-methods.html] employ will be used.



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