zhengruifeng commented on pull request #31086:
URL: https://github.com/apache/spark/pull/31086#issuecomment-756524483
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>
scala>
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>
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>
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)
```
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