19 register_parameters();
36 int32_t num_features = simple_features->get_num_features();
38 "number of feature vectors should be at least 2!\n");
40 SG_INFO(
"Extracting min and range values for each feature\n")
45 for (
index_t i = 0; i < num_features; i++)
59 if ((cur_max - cur_min) > 0) {
61 m_range[i] = 1.0/(cur_max - cur_min);
98 return feature_matrix;
115 void CRescaleFeatures::register_parameters()
virtual ~CRescaleFeatures()
virtual int32_t get_num_vectors() const =0
virtual SGVector< float64_t > apply_to_feature_vector(SGVector< float64_t > vector)
Template class DensePreprocessor, base class for preprocessors (cf. CPreprocessor) that apply to CDen...
virtual SGMatrix< float64_t > apply_to_feature_matrix(CFeatures *features)
virtual EFeatureClass get_feature_class() const =0
T * get_column_vector(index_t col) const
static void vec1_plus_scalar_times_vec2(T *vec1, const T scalar, const T *vec2, int32_t n)
x=x+alpha*y
SGVector< float64_t > m_min
all of classes and functions are contained in the shogun namespace
SGVector< float64_t > m_range
The class Features is the base class of all feature objects.
virtual EFeatureType get_feature_type() const =0
void add(const SGVector< T > x)