11 #ifndef _ONLINELINEARCLASSIFIER_H__
12 #define _ONLINELINEARCLASSIFIER_H__
78 for (int32_t i=0; i<
w_dim; i++)
101 memcpy(
w, src_w,
size_t(src_w_dim)*
sizeof(
float32_t));
115 for (int32_t i=0; i<src_w_dim; i++)
143 virtual bool load(FILE* srcfile);
150 virtual bool save(FILE* dstfile);
212 virtual const char*
get_name()
const {
return "OnlineLinearMachine"; }
Class OnlineLinearMachine is a generic interface for linear machines like classifiers which work thro...
virtual SGVector< float32_t > get_w()
The class Labels models labels, i.e. class assignments of objects.
static const float64_t INFTY
infinity
virtual bool save(FILE *dstfile)
#define SG_NOTIMPLEMENTED
virtual void set_w(float64_t *src_w, int32_t src_w_dim)
virtual CLabels * apply()
A generic learning machine interface.
virtual float32_t get_bias()
virtual void set_features(CStreamingDotFeatures *feat)
virtual float32_t apply_to_current_example()
Streaming features that support dot products among other operations.
virtual float64_t apply(int32_t vec_idx)
get output for example "vec_idx"
virtual CStreamingDotFeatures * get_features()
virtual void get_w(float64_t *&dst_w, int32_t &dst_dims)
CStreamingDotFeatures * features
The class Features is the base class of all feature objects.
virtual bool load(FILE *srcfile)
virtual const char * get_name() const
virtual void set_w(float32_t *src_w, int32_t src_w_dim)
virtual ~COnlineLinearMachine()
virtual void get_w(float32_t *&dst_w, int32_t &dst_dims)
#define SG_MALLOC(type, len)
virtual void set_bias(float32_t b)