36 void CLinearRidgeRegression::init()
55 SG_ERROR(
"Number of training vectors does not match number of labels\n")
58 SG_ERROR(
"Expected Dense Features\n")
75 for (int32_t i=0; i<num_feat; i++)
78 for (int32_t i=0; i<num_vec; i++)
83 cblas_dger(CblasColMajor, num_feat,num_feat, 1.0, v.
vector,1,
91 clapack_dposv(CblasRowMajor,CblasUpper, num_feat, 1, kernel_matrix.
matrix, num_feat,
Real Labels are real-valued labels.
virtual void set_w(const SGVector< float64_t > src_w)
The class Labels models labels, i.e. class assignments of objects.
virtual int32_t get_num_labels() const =0
virtual int32_t get_num_vectors() const =0
int32_t get_num_features() const
ST * get_feature_vector(int32_t num, int32_t &len, bool &dofree)
virtual bool save(FILE *dstfile)
void free_feature_vector(ST *feat_vec, int32_t num, bool dofree)
virtual void set_features(CDotFeatures *feat)
virtual EFeatureClass get_feature_class() const =0
Class LinearMachine is a generic interface for all kinds of linear machines like classifiers.
all of classes and functions are contained in the shogun namespace
The class Features is the base class of all feature objects.
virtual bool load(FILE *srcfile)
virtual bool train_machine(CFeatures *data=NULL)
virtual void set_labels(CLabels *lab)
virtual int32_t get_num_vectors() const
virtual EFeatureType get_feature_type() const =0