, including all inherited members.
| activ_func | CvANN_MLP | [protected] |
| calc_activ_func(CvMat *xf, const double *bias) const | CvANN_MLP | [protected, virtual] |
| calc_activ_func_deriv(CvMat *xf, CvMat *deriv, const double *bias) const | CvANN_MLP | [protected, virtual] |
| calc_input_scale(const CvVectors *vecs, int flags) | CvANN_MLP | [protected, virtual] |
| calc_output_scale(const CvVectors *vecs, int flags) | CvANN_MLP | [protected, virtual] |
| clear() | CvANN_MLP | [virtual] |
| create(const CvMat *layerSizes, int activateFunc=CvANN_MLP::SIGMOID_SYM, double fparam1=0, double fparam2=0) | CvANN_MLP | [virtual] |
| create(const cv::Mat &layerSizes, int activateFunc=CvANN_MLP::SIGMOID_SYM, double fparam1=0, double fparam2=0) | CvANN_MLP | [virtual] |
| CvANN_MLP() | CvANN_MLP | |
| CvANN_MLP(const CvMat *layerSizes, int activateFunc=CvANN_MLP::SIGMOID_SYM, double fparam1=0, double fparam2=0) | CvANN_MLP | |
| CvANN_MLP(const cv::Mat &layerSizes, int activateFunc=CvANN_MLP::SIGMOID_SYM, double fparam1=0, double fparam2=0) | CvANN_MLP | |
| CvStatModel() | CvStatModel | |
| default_model_name | CvStatModel | [protected] |
| f_param1 | CvANN_MLP | [protected] |
| f_param2 | CvANN_MLP | [protected] |
| GAUSSIAN enum value | CvANN_MLP | |
| get_layer_count() | CvANN_MLP | [inline] |
| get_layer_sizes() | CvANN_MLP | [inline] |
| get_weights(int layer) | CvANN_MLP | [inline] |
| IDENTITY enum value | CvANN_MLP | |
| init_weights() | CvANN_MLP | [protected, virtual] |
| layer_sizes | CvANN_MLP | [protected] |
| load(const char *filename, const char *name=0) | CvStatModel | [virtual] |
| max_buf_sz | CvANN_MLP | [protected] |
| max_count | CvANN_MLP | [protected] |
| max_val | CvANN_MLP | [protected] |
| max_val1 | CvANN_MLP | [protected] |
| min_val | CvANN_MLP | [protected] |
| min_val1 | CvANN_MLP | [protected] |
| NO_INPUT_SCALE enum value | CvANN_MLP | |
| NO_OUTPUT_SCALE enum value | CvANN_MLP | |
| params | CvANN_MLP | [protected] |
| predict(const CvMat *inputs, CV_OUT CvMat *outputs) const | CvANN_MLP | [virtual] |
| predict(const cv::Mat &inputs, cv::Mat &outputs) const | CvANN_MLP | [virtual] |
| prepare_to_train(const CvMat *_inputs, const CvMat *_outputs, const CvMat *_sample_weights, const CvMat *sampleIdx, CvVectors *_ivecs, CvVectors *_ovecs, double **_sw, int _flags) | CvANN_MLP | [protected, virtual] |
| read(CvFileStorage *fs, CvFileNode *node) | CvANN_MLP | [virtual] |
| read_params(CvFileStorage *fs, CvFileNode *node) | CvANN_MLP | [protected, virtual] |
| rng | CvANN_MLP | [protected] |
| sample_weights | CvANN_MLP | [protected] |
| save(const char *filename, const char *name=0) const | CvStatModel | [virtual] |
| scale_input(const CvMat *_src, CvMat *_dst) const | CvANN_MLP | [protected, virtual] |
| scale_output(const CvMat *_src, CvMat *_dst) const | CvANN_MLP | [protected, virtual] |
| set_activ_func(int _activ_func=SIGMOID_SYM, double _f_param1=0, double _f_param2=0) | CvANN_MLP | [protected, virtual] |
| SIGMOID_SYM enum value | CvANN_MLP | |
| train(const CvMat *inputs, const CvMat *outputs, const CvMat *sampleWeights, const CvMat *sampleIdx=0, CvANN_MLP_TrainParams params=CvANN_MLP_TrainParams(), int flags=0) | CvANN_MLP | [virtual] |
| train(const cv::Mat &inputs, const cv::Mat &outputs, const cv::Mat &sampleWeights, const cv::Mat &sampleIdx=cv::Mat(), CvANN_MLP_TrainParams params=CvANN_MLP_TrainParams(), int flags=0) | CvANN_MLP | [virtual] |
| train_backprop(CvVectors _ivecs, CvVectors _ovecs, const double *_sw) | CvANN_MLP | [protected, virtual] |
| train_rprop(CvVectors _ivecs, CvVectors _ovecs, const double *_sw) | CvANN_MLP | [protected, virtual] |
| UPDATE_WEIGHTS enum value | CvANN_MLP | |
| wbuf | CvANN_MLP | [protected] |
| weights | CvANN_MLP | [protected] |
| write(CvFileStorage *storage, const char *name) const | CvANN_MLP | [virtual] |
| write_params(CvFileStorage *fs) const | CvANN_MLP | [protected, virtual] |
| ~CvANN_MLP() | CvANN_MLP | [virtual] |
| ~CvStatModel() | CvStatModel | [virtual] |