LinearMachine.cpp

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00001 /*
00002  * This program is free software; you can redistribute it and/or modify
00003  * it under the terms of the GNU General Public License as published by
00004  * the Free Software Foundation; either version 3 of the License, or
00005  * (at your option) any later version.
00006  *
00007  * Written (W) 1999-2009 Soeren Sonnenburg
00008  * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
00009  */
00010 
00011 #include <shogun/machine/LinearMachine.h>
00012 #include <shogun/labels/RegressionLabels.h>
00013 #include <shogun/base/Parameter.h>
00014 
00015 using namespace shogun;
00016 
00017 CLinearMachine::CLinearMachine()
00018 : CMachine(), bias(0), features(NULL)
00019 {
00020     init();
00021 }
00022 
00023 CLinearMachine::CLinearMachine(CLinearMachine* machine) : CMachine(),
00024     bias(0), features(NULL)
00025 {
00026     set_w(machine->get_w().clone());
00027     set_bias(machine->get_bias());
00028 
00029     init();
00030 }
00031 
00032 void CLinearMachine::init()
00033 {
00034     SG_ADD(&w, "w", "Parameter vector w.", MS_NOT_AVAILABLE);
00035     SG_ADD(&bias, "bias", "Bias b.", MS_NOT_AVAILABLE);
00036     SG_ADD((CSGObject**) &features, "features", "Feature object.",
00037         MS_NOT_AVAILABLE);
00038 }
00039 
00040 
00041 CLinearMachine::~CLinearMachine()
00042 {
00043     SG_UNREF(features);
00044 }
00045 
00046 float64_t CLinearMachine::apply_one(int32_t vec_idx)
00047 {
00048     return features->dense_dot(vec_idx, w.vector, w.vlen) + bias;
00049 }
00050 
00051 CRegressionLabels* CLinearMachine::apply_regression(CFeatures* data)
00052 {
00053     SGVector<float64_t> outputs = apply_get_outputs(data);
00054     return new CRegressionLabels(outputs);
00055 }
00056 
00057 CBinaryLabels* CLinearMachine::apply_binary(CFeatures* data)
00058 {
00059     SGVector<float64_t> outputs = apply_get_outputs(data);
00060     return new CBinaryLabels(outputs);
00061 }
00062 
00063 SGVector<float64_t> CLinearMachine::apply_get_outputs(CFeatures* data)
00064 {
00065     if (data)
00066     {
00067         if (!data->has_property(FP_DOT))
00068             SG_ERROR("Specified features are not of type CDotFeatures\n");
00069 
00070         set_features((CDotFeatures*) data);
00071     }
00072 
00073     if (!features)
00074         return SGVector<float64_t>();
00075 
00076     int32_t num=features->get_num_vectors();
00077     ASSERT(num>0);
00078     ASSERT(w.vlen==features->get_dim_feature_space());
00079 
00080     float64_t* out=SG_MALLOC(float64_t, num);
00081     features->dense_dot_range(out, 0, num, NULL, w.vector, w.vlen, bias);
00082     return SGVector<float64_t>(out,num);
00083 }
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SHOGUN Machine Learning Toolbox - Documentation