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70 lines
1.9 KiB
C++
70 lines
1.9 KiB
C++
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#ifndef MLPP_MANN_H
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#define MLPP_MANN_H
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#include "core/math/math_defs.h"
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#include "core/object/reference.h"
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#include "../regularization/reg.h"
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#include "../lin_alg/mlpp_matrix.h"
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#include "../lin_alg/mlpp_vector.h"
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#include "../hidden_layer/hidden_layer.h"
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#include "../multi_output_layer/multi_output_layer.h"
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class MLPPMANN : public Reference {
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GDCLASS(MLPPMANN, Reference);
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public:
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/*
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Ref<MLPPMatrix> get_input_set();
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void set_input_set(const Ref<MLPPMatrix> &val);
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Ref<MLPPMatrix> get_output_set();
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void set_output_set(const Ref<MLPPMatrix> &val);
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*/
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Ref<MLPPMatrix> model_set_test(const Ref<MLPPMatrix> &X);
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Ref<MLPPVector> model_test(const Ref<MLPPVector> &x);
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void gradient_descent(real_t learning_rate, int max_epoch, bool ui = false);
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real_t score();
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void save(const String &file_name);
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void add_layer(int n_hidden, MLPPActivation::ActivationFunction activation, MLPPUtilities::WeightDistributionType weight_init = MLPPUtilities::WEIGHT_DISTRIBUTION_TYPE_DEFAULT, MLPPReg::RegularizationType reg = MLPPReg::REGULARIZATION_TYPE_NONE, real_t lambda = 0.5, real_t alpha = 0.5);
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void add_output_layer(MLPPActivation::ActivationFunction activation, MLPPCost::CostTypes loss, MLPPUtilities::WeightDistributionType weight_init = MLPPUtilities::WEIGHT_DISTRIBUTION_TYPE_DEFAULT, MLPPReg::RegularizationType reg = MLPPReg::REGULARIZATION_TYPE_NONE, real_t lambda = 0.5, real_t alpha = 0.5);
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bool is_initialized();
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void initialize();
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MLPPMANN(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPMatrix> &p_output_set);
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MLPPMANN();
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~MLPPMANN();
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private:
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real_t cost(const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y);
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void forward_pass();
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static void _bind_methods();
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Ref<MLPPMatrix> _input_set;
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Ref<MLPPMatrix> _output_set;
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Ref<MLPPMatrix> _y_hat;
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Vector<Ref<MLPPHiddenLayer>> _network;
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Ref<MLPPMultiOutputLayer> _output_layer;
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int _n;
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int _k;
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int _n_output;
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bool _initialized;
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};
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#endif /* MANN_hpp */ |