spark AbsoluteError 源码
spark AbsoluteError 代码
文件路径：/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/AbsoluteError.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.
*/
package org.apache.spark.mllib.tree.loss
import org.apache.spark.annotation.Since
/**
* Class for absolute error loss calculation (for regression).
*
* The absolute (L1) error is defined as:
* |y - F(x)|
* where y is the label and F(x) is the model prediction for features x.
*/
@Since("1.2.0")
object AbsoluteError extends Loss {
/**
* Method to calculate the gradients for the gradient boosting calculation for least
* absolute error calculation.
* The gradient with respect to F(x) is: sign(F(x) - y)
* @param prediction Predicted label.
* @param label True label.
* @return Loss gradient
*/
@Since("1.2.0")
override def gradient(prediction: Double, label: Double): Double = {
if (label - prediction < 0) 1.0 else -1.0
}
override private[spark] def computeError(prediction: Double, label: Double): Double = {
val err = label - prediction
math.abs(err)
}
}
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