content: /*
   * Tencent is pleased to support the open source community by making Angel available.
   *
   * Copyright (C) 2017-2018 THL A29 Limited, a Tencent company. All rights reserved.
   *
   * Licensed 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
   *
   * https://opensource.org/licenses/Apache-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 com.tencent.angel.ml.GBDT.metric;
  
  /**
   * Description: the metric of logistic loss
   */
  
  public class LogLossMetric implements EvalMetric {
  
    /**
     * return name of metric
     *
     * @return the name
     */
    @Override public String getName() {
      return "logloss";
    }
  
    /**
     * evaluate a specific metric for instances
     *
     * @param predProbs the probability predictions
     * @param labels    the labels
     * @return the eval metric
     */
    @Override public float eval(float[] predProbs, float[] labels) {
      float errSum = 0.0f;
      for (int i = 0; i < predProbs.length; i++) {
        errSum += evalOne(predProbs[i], labels[i]);
      }
      return errSum / predProbs.length;
    }
  
    /**
     * evaluate a specific metric for one instance
     *
     * @param predProb the probability prediction
     * @param label    the label
     * @return the eval metric
     */
    @Override public float evalOne(float predProb, float label) {
      float eps = 1e-16f;
      float pneg = 1.0f - predProb;
      if (predProb < eps) {
        return -label * (float) Math.log(eps) - (1.0f - label) * (float) Math.log(1.0f - eps);
      } else if (pneg < eps) {
        return -label * (float) Math.log(1.0f - eps) - (1.0f - label) * (float) Math.log(eps);
      } else {
        return -label * (float) Math.log(predProb) - (1.0f - label) * (float) Math.log(pneg);
      }
    }
  
  
  }