[
https://issues.apache.org/jira/browse/SPARK-34045?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
zhengruifeng updated SPARK-34045:
---------------------------------
Description:
featuresCol of submodels maybe changed in transform:
{code:java}
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)
{code}
was:
featuresCol of submodels maybe changed in transform:
{code:java}
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)
{code}
> OneVsRestModel.transform should not call setter of submodels
> ------------------------------------------------------------
>
> Key: SPARK-34045
> URL: https://issues.apache.org/jira/browse/SPARK-34045
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.2.0
> Reporter: zhengruifeng
> Priority: Minor
>
> featuresCol of submodels maybe changed in transform:
> {code:java}
> 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)
> {code}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
