#include <lwpr.h>
Data Fields | |
int | nIn |
Number N of input dimensions. | |
int | nInStore |
Storage-size of any N-vector, for aligment purposes. | |
int | nOut |
Number M of output dimensions. | |
int | n_data |
Number of training data the model has seen. | |
double * | mean_x |
Mean of all training data the model has seen (Nx1). | |
double * | var_x |
Mean of all training data the model has seen (Nx1). | |
char * | name |
An optional description of the model (Mx1). | |
int | diag_only |
Flag that determines whether distance matrices are handled as diagonal-only. | |
int | meta |
Flag that determines wheter 2nd order updates to LWPR_ReceptiveField.M are computed. | |
double | meta_rate |
Learning rate for 2nd order updates. | |
double | penalty |
Penalty factor used within distance metric updates. | |
double * | init_alpha |
Initial learning rate for 2nd order distance metric updates (NxN). | |
double * | norm_in |
Input normalisation (Nx1). Adjust this to the expected variation of your data. | |
double * | norm_out |
Output normalisation. Adjust this to the expected variation of your output data. | |
double * | init_D |
Initial distance metric (NxN). This often requires some tuning (NxN). | |
double * | init_M |
Cholesky factorisation of LWPR_Model.init_D (NxN). | |
double | w_gen |
Threshold that determines the minimum activation before a new RF is created. | |
double | w_prune |
Threshold that determines above which (second highest) activation a RF is pruned. | |
double | init_lambda |
Initial forgetting factor. | |
double | final_lambda |
Final forgetting factor. | |
double | tau_lambda |
This parameter describes the annealing schedule of the forgetting factor. | |
double | init_S2 |
Initial value for sufficient statistics LWPR_ReceptiveField.SSs2. | |
double | add_threshold |
Threshold that determines when a new PLS regression axis is added. | |
LWPR_Kernel | kernel |
Describes which kernel function is used (Gaussian or BiSquare). | |
int | update_D |
Flag that determines whether distance metric updates are performed (default: 1). | |
LWPR_SubModel * | sub |
Array of SubModels, one for each output dimension. | |
struct LWPR_Workspace * | ws |
Array of Workspaces, one for each thread (cf. LWPR_NUM_THREADS). | |
double * | storage |
Pointer to allocated memory. Do not touch. | |
double * | xn |
Used to hold a normalised input vector (Nx1). | |
double * | yn |
Used to hold a normalised output vector (Nx1). | |
int | isPersistent |
MEX-specific flag which determines whether this LWPR_Model is persistent. |
This structure contains flags and initial values that determine the behaviour of the LWPR algorithm, and also provides some statistics about the model.
It should always be initialised with lwpr_init_model, and destroyed with lwpr_free_model. Note that both functions do not allocate/free the space for the LWPR_Model itself.
MEX-specific flag which determines whether this LWPR_Model is persistent.
This variable is only included in the LWPR_Model structure if the library is compiled with the directive MATLAB (i.e. for MEX-file usage). In that case, isPersistent=1 indicates that the LWPR model should be protected from automatic memory cleanups as performed by MATLAB.