FST::Data_Scaler_to01< DATATYPE > Class Template Reference

Implements data normalization (of all feature values) to interval [0,1]. More...

#include <data_scaler_to01.hpp>

Inheritance diagram for FST::Data_Scaler_to01< DATATYPE >:

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Collaboration diagram for FST::Data_Scaler_to01< DATATYPE >:

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List of all members.

Public Member Functions
	Data_Scaler_to01 (const int dims=1)
	Data_Scaler_to01 (const DATATYPE missing_val_code, const int dims)
	Data_Scaler_to01 (const Data_Scaler_to01 &ds)
virtual int	learn_loops () const
virtual bool	startFirstLoop ()
virtual bool	startNextLoop ()
virtual void	learn (const DATATYPE &value)
virtual DATATYPE	scale (const DATATYPE &value)
	return the scaled value
virtual void	scale_inplace (DATATYPE &value)
	scale the value in place
virtual std::ostream &	print (std::ostream &os) const
Protected Attributes
bool	first_learn
DATATYPE	min
DATATYPE	max
bool	missing_values
const DATATYPE	_missing_val_code
long	count
DATATYPE	sum
DATATYPE	avg

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Detailed Description

template<typename DATATYPE>
class FST::Data_Scaler_to01< DATATYPE >

Implements data normalization (of all feature values) to interval [0,1].

Note:

this implementation supports only scaling of one-dimensional data, thus is applicable only to scale feature values individually and independently for each other feature

optionally substitutes missing values by the mean of those values that are available (separately per feature). Missing values are assumed to be coded by dedicated numerical value 'missing_val_code'.

Examples:

demo53.cpp.

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

• data_scaler_to01.hpp