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.objective;
  
  import com.tencent.angel.ml.GBDT.algo.RegTree.GradPair;
  import com.tencent.angel.ml.GBDT.algo.RegTree.RegTDataStore;
  
  import java.util.List;
  
  /**
   * interface of objective function Description:
   */
  
  public interface ObjFunc {
  
    /**
     * get gradient over each of predictions, given existing information. preds: prediction of current
     * round info information about labels, weights, groups in rank iteration current iteration
     * number. return:_gpair output of get gradient, saves gradient and second order gradient in
     */
    GradPair[] calGrad(float[] preds, RegTDataStore info, int iteration);
  
    /**
     * transform prediction values, this is only called when Prediction is called preds: prediction
     * values, saves to this vector as well
     */
    void transPred(float[] preds);
  
    /**
     * transform prediction values, this is only called when Eval is called usually it redirect to
     * transPred preds: prediction values, saves to this vector as well
     */
    void transEval(float[] preds);
  
    /**
     * transform probability value back to margin this is used to transform user-set base_score back
     * to margin used by gradient boosting
     */
    float prob2Margin(float base_score);
  
    // return the default evaluation metric for the objective
    String defaultEvalMetric();
  }