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71 lines
1.8 KiB
71 lines
1.8 KiB
#pragma once
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class SplitEvaluator {
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public:
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SplitEvaluator(bool normalize)
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: normalize_(normalize) {}
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virtual ~SplitEvaluator() {}
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virtual float Eval(const std::vector<TrainDatum>& lefttargets, const std::vector<TrainDatum>& righttargets, int depth) const {
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float purity_left = Purity(lefttargets, depth);
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float purity_right = Purity(righttargets, depth);
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float normalize_left = 1.0;
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float normalize_right = 1.0;
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if(normalize_) {
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unsigned int n_left = lefttargets.size();
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unsigned int n_right = righttargets.size();
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unsigned int n_total = n_left + n_right;
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normalize_left = float(n_left) / float(n_total);
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normalize_right = float(n_right) / float(n_total);
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}
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float purity = purity_left * normalize_left + purity_right * normalize_right;
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return purity;
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}
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protected:
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virtual float Purity(const std::vector<TrainDatum>& targets, int depth) const = 0;
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protected:
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bool normalize_;
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};
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class ClassificationIGSplitEvaluator : public SplitEvaluator {
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public:
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ClassificationIGSplitEvaluator(bool normalize, int n_classes)
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: SplitEvaluator(normalize), n_classes_(n_classes) {}
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virtual ~ClassificationIGSplitEvaluator() {}
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protected:
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virtual float Purity(const std::vector<TrainDatum>& targets, int depth) const {
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if(targets.size() == 0) return 0;
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std::vector<int> ps;
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ps.resize(n_classes_, 0);
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for(auto target : targets) {
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auto ctarget = std::static_pointer_cast<ClassificationTarget>(target.optimize_target);
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ps[ctarget->cl()] += 1;
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}
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float h = 0;
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for(int cl = 0; cl < n_classes_; ++cl) {
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float fi = float(ps[cl]) / float(targets.size());
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if(fi > 0) {
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h = h - fi * std::log(fi);
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}
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}
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return h;
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}
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private:
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int n_classes_;
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};
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