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https://issues.apache.org/jira/browse/SPARK-16863?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15405333#comment-15405333
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zhengruifeng commented on SPARK-16863:
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[SPARK-16851] add checking for
{{ProbabilisticClassificationModel.setThreshoulds}}.
I just found that {{ProbabilisticClassifier.fit}} also need to check
threshoulds' length if {{ProbabilisticClassifier.setThreshoulds}} is called, so
I open this JIRA.
> ProbabilisticClassifier.fit check threshoulds' length
> -----------------------------------------------------
>
> Key: SPARK-16863
> URL: https://issues.apache.org/jira/browse/SPARK-16863
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: zhengruifeng
> Priority: Minor
>
> {code}
> val path =
> "./spark-2.0.0-bin-hadoop2.7/data/mllib/sample_multiclass_classification_data.txt"
> val data = spark.read.format("libsvm").load(path)
> val rf = new RandomForestClassifier
> rf.setThresholds(Array(0.1,0.2,0.3,0.4,0.5))
> val rfm = rf.fit(data)
> rfm: org.apache.spark.ml.classification.RandomForestClassificationModel =
> RandomForestClassificationModel (uid=rfc_fec31a5b954d) with 20 trees
> rfm.numClasses
> res2: Int = 3
> rfm.getThresholds
> res3: Array[Double] = Array(0.1, 0.2, 0.3, 0.4, 0.5)
> rfm.transform(data)
> java.lang.IllegalArgumentException: requirement failed:
> RandomForestClassificationModel.transform() called with non-matching
> numClasses and thresholds.length. numClasses=3, but thresholds has length 5
> at scala.Predef$.require(Predef.scala:224)
> at
> org.apache.spark.ml.classification.ProbabilisticClassificationModel.transform(ProbabilisticClassifier.scala:101)
> ... 72 elided
> {code}
> {{ProbabilisticClassifier.fit()}} should throw some exception if it's
> threshoulds is set incorrectly.
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