ECOCPAK v0.9
Functions
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.

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.
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