Minor Description
featuresCol of submodels maybe changed in transform:
scala> val df = spark.read.format("libsvm").load("/d0/Dev/Opensource/spark/data/mllib/sample_multiclass_classification_data.txt") 21/01/08 09:52:01 WARN LibSVMFileFormat: 'numFeatures' option not specified, determining the number of features by going though the input. If you know the number in advance, please specify it via 'numFeatures' option to avoid the extra scan. df: org.apache.spark.sql.DataFrame = [label: double, features: vector] scala> val lr = new LogisticRegression().setMaxIter(1).setTol(1E-6).setFitIntercept(true) lr: org.apache.spark.ml.classification.LogisticRegression = logreg_3003cb3321a1 scala> val ovr = new OneVsRest().setClassifier(lr) ovr: org.apache.spark.ml.classification.OneVsRest = oneVsRest_b2ec3ec45dbf scala> val ovrm = ovr.fit(df) 21/01/08 09:52:05 WARN BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeSystemBLAS 21/01/08 09:52:05 WARN BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeRefBLAS ovrm: org.apache.spark.ml.classification.OneVsRestModel = OneVsRestModel: uid=oneVsRest_b2ec3ec45dbf, classifier=logreg_3003cb3321a1, numClasses=3, numFeatures=4 scala> val df2 = df.withColumnRenamed("features", "features2") df2: org.apache.spark.sql.DataFrame = [label: double, features2: vector] scala> ovrm.setFeaturesCol("features2") res0: ovrm.type = OneVsRestModel: uid=oneVsRest_b2ec3ec45dbf, classifier=logreg_3003cb3321a1, numClasses=3, numFeatures=4 scala> ovrm.models.map(_.getFeaturesCol) res1: Array[String] = Array(features, features, features) scala> ovrm.transform(df2) res2: org.apache.spark.sql.DataFrame = [label: double, features2: vector ... 2 more fields] scala> ovrm.models.map(_.getFeaturesCol) res3: Array[String] = Array(features2, features2, features2)
