[ https://issues.apache.org/jira/browse/SPARK-16851?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Yanbo Liang updated SPARK-16851: -------------------------------- Assignee: zhengruifeng > Incorrect threshould length in 'setThresholds()' evoke Exception > ----------------------------------------------------------------- > > Key: SPARK-16851 > URL: https://issues.apache.org/jira/browse/SPARK-16851 > Project: Spark > Issue Type: Improvement > Components: ML > Reporter: zhengruifeng > Assignee: zhengruifeng > Priority: Trivial > Fix For: 2.1.0 > > > {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() > val model = rf.fit(data) > model.numClasses > res48: Int = 3 > model.setThresholds(Array(0.5,0.1)) > res49: org.apache.spark.ml.classification.RandomForestClassificationModel = > RandomForestClassificationModel (uid=rfc_b39da354ac8b) with 20 trees > model.transform(data) > java.lang.IllegalArgumentException: requirement failed: > RandomForestClassificationModel.transform() called with non-matching > numClasses and thresholds.length. numClasses=3, but thresholds has length 2 > at scala.Predef$.require(Predef.scala:224) > at > org.apache.spark.ml.classification.ProbabilisticClassificationModel.transform(ProbabilisticClassifier.scala:101) > ... 58 elided > {code} > Although model set with wrong threshoulds will fail in prediction, it maybe > nice to evoke exception earlier in {{setThreshoulds}} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org