Fn_decode

Functions
void	ecocpak::decode (const mat &Xt, const uvec &lt, const imat &coding_matrix, const vector< Classifier * > &classifiers_vector, const vector< ClassData > &classes_vector, const int decoding_option, uvec &predictions, u32 &n_missed, double &error, umat &confussion)
	Decoding procedure.
void	decode (const mat &Xt, const uvec &lt, const imat &coding_matrix, const vector< Classifier * > &classifiers_vector, const vector< ClassData > &classes_vector, const int decoding_option, uvec &predictions, u32 &n_missed, double &error, umat &confussion)
	Decoding procedure.

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Function Documentation

void ecocpak::decode	(	const mat &	Xt,
		const uvec &	lt,
		const imat &	coding_matrix,
		const vector< Classifier * > &	classifiers_vector,
		const vector< ClassData > &	classes_vector,
		const int	decoding_option,
		uvec &	predictions,
		u32 &	n_missed,
		double &	error,
		umat &	confussion
	)

Decoding procedure.

• Input Arguments:
  • Xt : A 2D input matrix where its rows represent the test sample vectors.
  • lt : sample labels.
  • coding_matrix : Coding matrix.
  • decoding_option : User's option specifying the type of decoding method that will be used.
  • classifiers_vector : Vector of trainned binary classifiers.
  • classes_vector : Vector of ClassData objects.

• Output Arguments:
  • predictions : Vector with predictions for each sample.
  • n_missed : Number of missclassified samples.
  • error : Total classification error.
  • confussion : Confussion matrix.

• Return Argument:
  • Void.

void decode	(	const mat &	Xt,
		const uvec &	lt,
		const imat &	coding_matrix,
		const vector< Classifier * > &	classifiers_vector,
		const vector< ClassData > &	classes_vector,
		const int	decoding_option,
		uvec &	predictions,
		u32 &	n_missed,
		double &	error,
		umat &	confussion
	)

Decoding procedure.

• Input Arguments:
  • Xt : A 2D input matrix where its rows represent the test sample vectors.
  • lt : sample labels.
  • coding_matrix : Coding matrix.
  • decoding_option : User's option specifying the type of decoding method that will be used.
  • classifiers_vector : Vector of trainned binary classifiers.
  • classes_vector : Vector of ClassData objects.

• Output Arguments:
  • predictions : Vector with predictions for each sample.
  • n_missed : Number of missclassified samples.
  • error : Total classification error.
  • confussion : Confussion matrix.

• Return Argument:
  • Void.