zhengruifeng created SPARK-16863: ------------------------------------ Summary: 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. -- 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