Fn_subdecoc

Functions
u32	ecocpak::subdecoc (const mat &training_samples, const icolvec &training_labels, const mat &testing_samples, const icolvec &testing_labels, const Threshold &thres, const int decoding_strategy, const int classifiers_type, const int criterion_option, const bool verbose, imat &coding_matrix, ofstream &verbose_output, double &execution_time)
	Discriminant Error Correcting Output Codes with subclasses (SUBDECOC) training and testing procedure .
u32	subdecoc (const mat &training_samples, const icolvec &training_labels, const mat &testing_samples, const icolvec &testing_labels, const Threshold &thres, const int decoding_strategy, const int classifiers_type, const int criterion_option, const bool verbose, imat &coding_matrix, ofstream &verbose_output, double &execution_time)
	Discriminant Error Correcting Output Codes with subclasses (SUBDECOC) training and testing procedure .

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Function Documentation

u32 ecocpak::subdecoc	(	const mat &	training_samples,
		const icolvec &	training_labels,
		const mat &	testing_samples,
		const icolvec &	testing_labels,
		const Threshold &	thres,
		const int	decoding_strategy,
		const int	classifiers_type,
		const int	criterion_option,
		const bool	verbose,
		imat &	coding_matrix,
		ofstream &	verbose_output,
		double &	execution_time
	)

Discriminant Error Correcting Output Codes with subclasses (SUBDECOC) training and testing procedure .

• Input Arguments:
  • training_samples : A 2D input matrix where its rows represent training sample vectors.
  • training_labels : The respective class labels of training_samples input matrix.
  • testing_samples : A 2D input matrix where its rows represent testing sample vectors.
  • testing_labels : The respective class labels of testing_samples input matrix.
  • thres : Threshold object.
  • decoding_strategy : User's option specifying the type of decoding method that will be used.
  • classifiers_type : Type of classifier.
  • criterion_option : Criterion option (FQMI or FLDR).

• Output Arguments:
  • coding_matrix : Coding matrix.
  • classifiers_vector : Vector of classifiers objects.
  • execution_time : Execution time.

• Return Argument:
  • Number of misclassified test samples.

u32 subdecoc	(	const mat &	training_samples,
		const icolvec &	training_labels,
		const mat &	testing_samples,
		const icolvec &	testing_labels,
		const Threshold &	thres,
		const int	decoding_strategy,
		const int	classifiers_type,
		const int	criterion_option,
		const bool	verbose,
		imat &	coding_matrix,
		ofstream &	verbose_output,
		double &	execution_time
	)

Discriminant Error Correcting Output Codes with subclasses (SUBDECOC) training and testing procedure .

• Input Arguments:
  • training_samples : A 2D input matrix where its rows represent training sample vectors.
  • training_labels : The respective class labels of training_samples input matrix.
  • testing_samples : A 2D input matrix where its rows represent testing sample vectors.
  • testing_labels : The respective class labels of testing_samples input matrix.
  • thres : Threshold object.
  • decoding_strategy : User's option specifying the type of decoding method that will be used.
  • classifiers_type : Type of classifier.
  • criterion_option : Criterion option (FQMI or FLDR).

• Output Arguments:
  • coding_matrix : Coding matrix.
  • classifiers_vector : Vector of classifiers objects.
  • execution_time : Execution time.

• Return Argument:
  • Number of misclassified test samples.