, including all inherited members.
| actf | jymlp::Mlp | [protected] |
| addErrorAndGradient(const vector< double > &input, const vector< double > &target, double coefficient, double *sqerror, double *error, vector< double > *mseGrad, vector< double > *meeGrad) const | jymlp::Mlp | |
| backwardEucSq(double coeff, double *destE, double *destG, double *workspace, ErrT errortype) const | jymlp::Mlp | |
| copyOutputVec(double *workspace) const | jymlp::Mlp | |
| errorVec(const vector< double > &target, double *workspace) const | jymlp::Mlp | |
| forward(const vector< double > &input, double *workspace) const | jymlp::Mlp | |
| fromStream(istream &ins) | jymlp::Mlp | |
| getNHiddenNeurons() const | jymlp::Mlp | |
| getNLayers() const | jymlp::Mlp | [inline] |
| getNNeurons(int layer) const | jymlp::Mlp | [inline] |
| getNumConnectedInputs() const | jymlp::Mlp | |
| getNumInputs() const | jymlp::Mlp | [inline] |
| getNumNonzeroWeights() const | jymlp::Mlp | |
| getNumOutputs() const | jymlp::Mlp | [inline] |
| getNWeights() const | jymlp::Mlp | [inline] |
| getWorkspaceSize() | jymlp::Mlp | |
| initRnd(double a, SynapticRandomizer &sr) | jymlp::Mlp | [protected] |
| Mlp() | jymlp::Mlp | |
| Mlp(const vector< size_t > &inneur) | jymlp::Mlp | |
| Mlp(const vector< size_t > &inneur, const vector< ActF > &iactf, const vector< double > &iweights) | jymlp::Mlp | |
| Mlp(const Mlp &other) | jymlp::Mlp | |
| Mlp(const vector< size_t > &inneur, const vector< ActF > &iactf, SynapticRandomizer &sr) | jymlp::Mlp | |
| nneur | jymlp::Mlp | [protected] |
| outputVecAsClassIndex(const double *workspace) const | jymlp::Mlp | |
| prettyPrint() | jymlp::Mlp | |
| prettyPrintGradient(const vector< double > &grad) const | jymlp::Mlp | |
| prettyPrintLayerActivations() | jymlp::Mlp | |
| prettyPrintLayerSizes() | jymlp::Mlp | |
| prettyPrintWeights() const | jymlp::Mlp | |
| toStream(ostream &o) | jymlp::Mlp | |
| update(double coeff, const double *wupd) | jymlp::Mlp | |
| weightDecayAbs(double coeff, double *destE, double *destG, bool excludeOutputBias) const | jymlp::Mlp | |
| weightDecaySq(double coeff, double *destE, double *destG, bool excludeOutputBias) const | jymlp::Mlp | |
| weights | jymlp::Mlp | [protected] |