spark OneHotEncoderExample 源码
spark OneHotEncoderExample 代码
文件路径：/examples/src/main/scala/org/apache/spark/examples/ml/OneHotEncoderExample.scala
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// scalastyle:off println
package org.apache.spark.examples.ml
// $example on$
import org.apache.spark.ml.feature.OneHotEncoder
// $example off$
import org.apache.spark.sql.SparkSession
object OneHotEncoderExample {
def main(args: Array[String]): Unit = {
val spark = SparkSession
.builder
.appName("OneHotEncoderExample")
.getOrCreate()
// Note: categorical features are usually first encoded with StringIndexer
// $example on$
val df = spark.createDataFrame(Seq(
(0.0, 1.0),
(1.0, 0.0),
(2.0, 1.0),
(0.0, 2.0),
(0.0, 1.0),
(2.0, 0.0)
)).toDF("categoryIndex1", "categoryIndex2")
val encoder = new OneHotEncoder()
.setInputCols(Array("categoryIndex1", "categoryIndex2"))
.setOutputCols(Array("categoryVec1", "categoryVec2"))
val model = encoder.fit(df)
val encoded = model.transform(df)
encoded.show()
// $example off$
spark.stop()
}
}
// scalastyle:on println
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