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Fix crashes.
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@ -580,7 +580,7 @@ Ref<MLPPVector> MLPPCost::dual_form_svm_deriv(const Ref<MLPPVector> &alpha, cons
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Ref<MLPPVector> alphaQDeriv = alg.mat_vec_multnv(Q, alpha);
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Ref<MLPPVector> one = alg.onevecnv(alpha->size());
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return alg.subtractionnm(alphaQDeriv, one);
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return alg.subtractionnv(alphaQDeriv, one);
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}
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MLPPCost::VectorCostFunctionPointer MLPPCost::get_cost_function_ptr_normal_vector(const MLPPCost::CostTypes cost) {
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@ -166,7 +166,7 @@ void MLPPDualSVC::save(const String &file_name) {
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//util.saveParameters(file_name, _alpha, _bias);
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}
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MLPPDualSVC::MLPPDualSVC(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPMatrix> &p_output_set, real_t p_C, KernelMethod p_kernel) {
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MLPPDualSVC::MLPPDualSVC(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPVector> &p_output_set, real_t p_C, KernelMethod p_kernel) {
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_input_set = p_input_set;
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_output_set = p_output_set;
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_n = p_input_set->size().y;
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@ -174,14 +174,16 @@ MLPPDualSVC::MLPPDualSVC(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPMatri
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_C = p_C;
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_kernel = p_kernel;
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_z.instance();
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_y_hat.instance();
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_alpha.instance();
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_y_hat->resize(_n);
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MLPPUtilities utils;
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_bias = utils.bias_initializationr();
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_alpha.instance();
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_alpha->resize(_n);
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utils.weight_initializationv(_alpha); // One alpha for all training examples, as per the lagrangian multipliers.
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@ -37,7 +37,7 @@ public:
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real_t score();
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void save(const String &file_name);
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MLPPDualSVC(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPMatrix> &p_output_set, real_t p_C, KernelMethod p_kernel = KERNEL_METHOD_LINEAR);
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MLPPDualSVC(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPVector> &p_output_set, real_t p_C, KernelMethod p_kernel = KERNEL_METHOD_LINEAR);
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MLPPDualSVC();
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~MLPPDualSVC();
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