[
https://issues.apache.org/jira/browse/SPARK-11259?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yanbo Liang updated SPARK-11259:
--------------------------------
Description:
Params.validateParams() can not be called automatically currently. Such as the
following code snippet will not throw exception which is not as expected.
{code}
val df = sqlContext.createDataFrame(
Seq(
(1, Vectors.dense(0.0, 1.0, 4.0), 1.0),
(2, Vectors.dense(1.0, 0.0, 4.0), 2.0),
(3, Vectors.dense(1.0, 0.0, 5.0), 3.0),
(4, Vectors.dense(0.0, 0.0, 5.0), 4.0))
).toDF("id", "features", "label")
val scaler = new MinMaxScaler()
.setInputCol("features")
.setOutputCol("features_scaled")
.setMin(10)
.setMax(0)
val pipeline = new Pipeline().setStages(Array(scaler))
pipeline.fit(df)
{code}
validateParams() should be called by
PipelineStage(Pipeline/Estimator/Transformer) automatically, so I propose to
put it in transformSchema().
was:
Params.validateParams() not be called automatically currently. Such as the
following code snippet will not throw exception which is not as expected.
{code}
val df = sqlContext.createDataFrame(
Seq(
(1, Vectors.dense(0.0, 1.0, 4.0), 1.0),
(2, Vectors.dense(1.0, 0.0, 4.0), 2.0),
(3, Vectors.dense(1.0, 0.0, 5.0), 3.0),
(4, Vectors.dense(0.0, 0.0, 5.0), 4.0))
).toDF("id", "features", "label")
val scaler = new MinMaxScaler()
.setInputCol("features")
.setOutputCol("features_scaled")
.setMin(10)
.setMax(0)
val pipeline = new Pipeline().setStages(Array(scaler))
pipeline.fit(df)
{code}
validateParams() should be called by
PipelineStage(Pipeline/Estimator/Transformer) automatically, so I propose to
put it in transformSchema().
> Params.validateParams() should be called automatically
> ------------------------------------------------------
>
> Key: SPARK-11259
> URL: https://issues.apache.org/jira/browse/SPARK-11259
> Project: Spark
> Issue Type: Bug
> Components: ML
> Reporter: Yanbo Liang
>
> Params.validateParams() can not be called automatically currently. Such as
> the following code snippet will not throw exception which is not as expected.
> {code}
> val df = sqlContext.createDataFrame(
> Seq(
> (1, Vectors.dense(0.0, 1.0, 4.0), 1.0),
> (2, Vectors.dense(1.0, 0.0, 4.0), 2.0),
> (3, Vectors.dense(1.0, 0.0, 5.0), 3.0),
> (4, Vectors.dense(0.0, 0.0, 5.0), 4.0))
> ).toDF("id", "features", "label")
> val scaler = new MinMaxScaler()
> .setInputCol("features")
> .setOutputCol("features_scaled")
> .setMin(10)
> .setMax(0)
> val pipeline = new Pipeline().setStages(Array(scaler))
> pipeline.fit(df)
> {code}
> validateParams() should be called by
> PipelineStage(Pipeline/Estimator/Transformer) automatically, so I propose to
> put it in transformSchema().
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