| _n_in | LearnModel | [protected] |
| _n_out | LearnModel | [protected] |
| back_propagate(const Input &, const DVEC &, DVEC &) | NNLayer | |
| c_error(const Output &out, const Output &y) const | LearnModel | [virtual] |
| clear_gradient() | NNLayer | |
| clone() const | NNLayer | [inline, virtual] |
| create() const | NNLayer | [inline, virtual] |
| Object::create(std::istream &) | Object | [static] |
| DVEC typedef | NNLayer | |
| dw | NNLayer | [protected] |
| exact_dimensions(UINT i, UINT o) const | LearnModel | [inline] |
| exact_dimensions(const LearnModel &l) const | LearnModel | [inline] |
| exact_dimensions(const DataSet &d) const | LearnModel | [inline] |
| feed_forward(const Input &, Output &) const | NNLayer | |
| get_output(UINT idx) const | LearnModel | [inline, virtual] |
| gradient() const | NNLayer | [inline] |
| id() const | NNLayer | [virtual] |
| id_t typedef | Object | |
| initialize() | NNLayer | [virtual] |
| LearnModel(UINT n_in=0, UINT n_out=0) | LearnModel | |
| logf | LearnModel | [protected] |
| margin(UINT i) const | LearnModel | [inline, virtual] |
| margin_norm() const | LearnModel | [inline, virtual] |
| margin_of(const Input &x, const Output &y) const | LearnModel | [virtual] |
| min_margin() const | LearnModel | |
| n_input() const | LearnModel | [inline] |
| n_output() const | LearnModel | [inline] |
| n_samples | LearnModel | [protected] |
| NIL_ID | Object | [protected, static] |
| NNLayer(UINT n_in=0, UINT n_unit=0) | NNLayer | [explicit] |
| NNLayer(std::istream &is) | NNLayer | [inline, explicit] |
| operator()(const Input &x) const | NNLayer | [inline, virtual] |
| ptd | LearnModel | [protected] |
| ptw | LearnModel | [protected] |
| r_error(const Output &out, const Output &y) const | LearnModel | [virtual] |
| reset() | LearnModel | [virtual] |
| serialize(std::ostream &, ver_list &) const | NNLayer | [protected, virtual] |
| Object::serialize(std::ostream &, ver_list &) const | Object | [protected, virtual] |
| set_dimensions(UINT, UINT) | LearnModel | [protected] |
| set_dimensions(const LearnModel &l) | LearnModel | [inline, protected] |
| set_dimensions(const DataSet &d) | LearnModel | [inline, protected] |
| set_log_file(FILE *f) | LearnModel | [inline] |
| set_train_data(const pDataSet &, const pDataWgt &=0) | LearnModel | [virtual] |
| set_weight(const WVEC &) | NNLayer | |
| set_weight_range(REAL min, REAL max) | NNLayer | [inline] |
| sig_der | NNLayer | [mutable, protected] |
| sigmoid(REAL) const | NNLayer | [protected, virtual] |
| sigmoid_deriv(REAL) const | NNLayer | [protected, virtual] |
| size() const | NNLayer | [inline] |
| support_weighted_data() const | LearnModel | [inline, virtual] |
| test_c_error(const pDataSet &) const | LearnModel | |
| test_r_error(const pDataSet &) const | LearnModel | |
| train() | NNLayer | [inline, virtual] |
| train_c_error() const | LearnModel | |
| train_data() const | LearnModel | [inline] |
| train_r_error() const | LearnModel | |
| unserialize(std::istream &, ver_list &, const id_t &=NIL_ID) | NNLayer | [protected, virtual] |
| Object::unserialize(std::istream &, ver_list &, const id_t &=NIL_ID) | Object | [inline, protected, virtual] |
| valid_dimensions(UINT, UINT) const | LearnModel | |
| valid_dimensions(const LearnModel &l) const | LearnModel | [inline] |
| ver_list typedef | Object | [protected] |
| ver_t typedef | Object | [protected] |
| w | NNLayer | [protected] |
| w_max | NNLayer | [protected] |
| w_min | NNLayer | [protected] |
| weight() const | NNLayer | [inline] |
| WVEC typedef | NNLayer | |
| ~Object() | Object | [inline, virtual] |
