spark AFTSurvivalRegressionExample 源码
spark AFTSurvivalRegressionExample 代码
文件路径：/examples/src/main/scala/org/apache/spark/examples/ml/AFTSurvivalRegressionExample.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.linalg.Vectors
import org.apache.spark.ml.regression.AFTSurvivalRegression
// $example off$
import org.apache.spark.sql.SparkSession
/**
* An example demonstrating AFTSurvivalRegression.
* Run with
* {{{
* bin/run-example ml.AFTSurvivalRegressionExample
* }}}
*/
object AFTSurvivalRegressionExample {
def main(args: Array[String]): Unit = {
val spark = SparkSession
.builder
.appName("AFTSurvivalRegressionExample")
.getOrCreate()
// $example on$
val training = spark.createDataFrame(Seq(
(1.218, 1.0, Vectors.dense(1.560, -0.605)),
(2.949, 0.0, Vectors.dense(0.346, 2.158)),
(3.627, 0.0, Vectors.dense(1.380, 0.231)),
(0.273, 1.0, Vectors.dense(0.520, 1.151)),
(4.199, 0.0, Vectors.dense(0.795, -0.226))
)).toDF("label", "censor", "features")
val quantileProbabilities = Array(0.3, 0.6)
val aft = new AFTSurvivalRegression()
.setQuantileProbabilities(quantileProbabilities)
.setQuantilesCol("quantiles")
val model = aft.fit(training)
// Print the coefficients, intercept and scale parameter for AFT survival regression
println(s"Coefficients: ${model.coefficients}")
println(s"Intercept: ${model.intercept}")
println(s"Scale: ${model.scale}")
model.transform(training).show(false)
// $example off$
spark.stop()
}
}
// scalastyle:on println
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