Ignore:
Timestamp:
10/26/15 20:44:41 (5 years ago)
Author:
gkronber
Message:

#2450: marked constructor of GBTModel obsolete and wrapped GBTModels in GBTModelSurrogates where necessary in the API. Removed an internal unused method from the API.

File:
1 edited

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  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeBuilder.cs

    r12700 r13065  
    119119    }
    120120
    121     // simple API produces a single regression tree optimizing sum of squared errors
    122     // this can be used if only a simple regression tree should be produced
    123     // for a set of trees use the method CreateRegressionTreeForGradientBoosting below
    124     //
    125     // r and m work in the same way as for alglib random forest
    126     // r is fraction of rows to use for training
    127     // m is fraction of variables to use for training
    128     public IRegressionModel CreateRegressionTree(int maxSize, double r = 0.5, double m = 0.5) {
    129       // subtract mean of y first
    130       var yAvg = y.Average();
    131       for (int i = 0; i < y.Length; i++) y[i] -= yAvg;
    132 
    133       var seLoss = new SquaredErrorLoss();
    134 
    135       var model = CreateRegressionTreeForGradientBoosting(y, curPred, maxSize, problemData.TrainingIndices.ToArray(), seLoss, r, m);
    136 
    137       return new GradientBoostedTreesModel(new[] { new ConstantRegressionModel(yAvg), model }, new[] { 1.0, 1.0 });
    138     }
    139 
    140121    // specific interface that allows to specify the target labels and the training rows which is necessary when for gradient boosted trees
    141122    public IRegressionModel CreateRegressionTreeForGradientBoosting(double[] y, double[] curPred, int maxSize, int[] idx, ILossFunction lossFunction, double r = 0.5, double m = 0.5) {
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