82 lines
2.7 KiB
C++
82 lines
2.7 KiB
C++
/* Copyright 2015-2017 Philippe Tillet
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*
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* Permission is hereby granted, free of charge, to any person obtaining
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* a copy of this software and associated documentation files
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* (the "Software"), to deal in the Software without restriction,
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* including without limitation the rights to use, copy, modify, merge,
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* publish, distribute, sublicense, and/or sell copies of the Software,
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* and to permit persons to whom the Software is furnished to do so,
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* subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
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* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
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* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
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* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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*/
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#include "isaac/runtime/predictors/random_forest.h"
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#include "rapidjson/to_array.hpp"
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namespace isaac
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{
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namespace runtime
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{
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namespace predictors
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{
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random_forest::tree::tree(rapidjson::Value const & treerep)
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{
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children_left_ = rapidjson::to_int_array<int>(treerep["children_left"]);
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children_right_ = rapidjson::to_int_array<int>(treerep["children_right"]);
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threshold_ = rapidjson::to_float_array<float>(treerep["threshold"]);
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feature_ = rapidjson::to_float_array<float>(treerep["feature"]);
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for(rapidjson::SizeType i = 0 ; i < treerep["value"].Size() ; i++)
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value_.push_back(rapidjson::to_float_array<float>(treerep["value"][i]));
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D_ = value_[0].size();
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}
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std::vector<float> const & random_forest::tree::predict(std::vector<int_t> const & x) const
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{
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int_t idx = 0;
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while(children_left_[idx]!=-1)
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idx = (x[feature_[idx]] <= threshold_[idx])?children_left_[idx]:children_right_[idx];
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return value_[idx];
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}
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size_t random_forest::tree::D() const { return D_; }
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random_forest::random_forest(rapidjson::Value const & estimators)
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{
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for(rapidjson::SizeType i = 0 ; i < estimators.Size() ; ++i)
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estimators_.push_back(tree(estimators[i]));
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D_ = estimators_.front().D();
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}
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std::vector<float> random_forest::predict(std::vector<int_t> const & x) const
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{
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std::vector<float> res(D_, 0);
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for(const auto & elem : estimators_)
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{
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std::vector<float> const & subres = elem.predict(x);
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for(size_t i = 0 ; i < D_ ; ++i)
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res[i] += subres[i];
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}
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for(size_t i = 0 ; i < D_ ; ++i)
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res[i] /= estimators_.size();
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return res;
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}
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std::vector<random_forest::tree> const & random_forest::estimators() const
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{ return estimators_; }
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}
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}
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}
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