spark-reviews mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From mengxr <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-13613] [ML] Provide ignored tests to ex...
Date Wed, 16 Mar 2016 07:30:23 GMT
Github user mengxr commented on a diff in the pull request:

    https://github.com/apache/spark/pull/11463#discussion_r56291297
  
    --- Diff: mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
---
    @@ -65,12 +51,23 @@ class LogisticRegressionSuite
           val xVariance = Array(0.6856, 0.1899, 3.116, 0.581)
     
           val testData =
    -        generateMultinomialLogisticInput(coefficients, xMean, xVariance, true, nPoints,
42)
    +        generateMultinomialLogisticInput(coefficients, xMean, xVariance,
    +          addIntercept = true, nPoints, 42)
     
           sqlContext.createDataFrame(sc.parallelize(testData, 4))
         }
       }
     
    +  /**
    +   * Enable the ignored test to export the dataset into CSV format,
    +   * so we can validate the training accuracy compared with R's glmnet package.
    +   */
    +  ignore("export test data into CSV format") {
    +    binaryDataset.rdd.map { case Row(label: Double, features: Vector) =>
    +      label + "," + features.toArray.mkString(",")
    +    }.repartition(1).saveAsTextFile("path")
    --- End diff --
    
    Do not use `path`. We can try `target/tmp/LogisticRegressionSuite/binaryDataset`.


---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastructure@apache.org or file a JIRA ticket
with INFRA.
---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org


Mime
View raw message