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StandardizationScaler Class Reference

Standardizes the data so the each feature has zero mean and unit variance. More...

Inheritance diagram for StandardizationScaler:
DataScaler

Public Member Functions

 StandardizationScaler (const MatrixXd &features, double norm_factor=1.0)
 Main constructor for StandardizationScaler. More...
 
- Public Member Functions inherited from DataScaler
void scale_samples (const MatrixXd &unscaled_samples, MatrixXd &scaled_samples)
 Apply scaling to a set of unscaled samples. More...
 
MatrixXd scale_samples (const MatrixXd &unscaled_samples)
 Apply scaling to a set of unscaled samples. More...
 
const VectorXdget_scaler_features_offsets () const
 Get the vector of offsets. More...
 
const VectorXdget_scaler_features_scale_factors () const
 Get the vector of scaling factors. More...
 
bool check_for_zero_scaler_factor (int index)
 Checks an individual scaler feature scale factor for being close to zero; If it is near zero, we can potentially run into a divide-by-zero error if not handled appropriately. More...
 

Additional Inherited Members

- Public Types inherited from DataScaler
enum  SCALER_TYPE { NONE, STANDARDIZATION, MEAN_NORMALIZATION, MINMAX_NORMALIZATION }
 Enumeration for supported types of DataScalers.
 
- Static Public Member Functions inherited from DataScaler
static SCALER_TYPE scaler_type (const std::string &scaler_name)
 Convert scaler name to enum type. More...
 
- Protected Attributes inherited from DataScaler
bool hasScaling
 Bool for whether or not the the scaling coefficients have been computed.
 
RowVectorXd scaledSample
 Vector for a single scaled sample - (num_features); avoids resize memory allocs.
 
VectorXd scalerFeaturesOffsets
 Vector of offsets - (num_features)
 
VectorXd scalerFeaturesScaleFactors
 Vector of scaling factors - (num_features)
 

Detailed Description

Standardizes the data so the each feature has zero mean and unit variance.

scaler_offsets = mean

scale_factors = standard_deviation/norm_factor

Constructor & Destructor Documentation

StandardizationScaler ( const MatrixXd features,
double  norm_factor = 1.0 
)

Main constructor for StandardizationScaler.

Parameters
[in]featuresUnscaled data matrix - (num_samples by num_features)
[in]norm_factorOptional scaling factor applied to each feature Has a default value of 1.0

References DataScaler::hasScaling, DataScaler::scaledSample, DataScaler::scalerFeaturesOffsets, and DataScaler::scalerFeaturesScaleFactors.


The documentation for this class was generated from the following files: