CCL Library
1.0
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This structure describes workspace for directly learning the policy model parameters using linear regression. More...
#include <ccl_learn_policy.h>
Data Fields | |
gsl_matrix * | HS |
Regularization basis for the H matrix. | |
gsl_matrix * | g |
Dot product of BX and U. | |
gsl_matrix * | Y_T |
Transpose of Y_. | |
gsl_matrix * | Y_ |
Output variable. | |
gsl_matrix * | H |
Dot product of BX and BX'. | |
gsl_matrix * | BX_T |
Transpose of BX_. | |
gsl_matrix * | BX_ |
High dimensionality of the input data. | |
gsl_matrix * | w_ |
Model parameters. | |
gsl_matrix * | pinvH1 |
Peuso inverse of H1. | |
gsl_vector * | V |
Eigen vector of H. | |
gsl_matrix * | D |
Diagobal matrix with eigen values of H. | |
int * | idx |
index | |
This structure describes workspace for directly learning the policy model parameters using linear regression.
This structure defines the worspace variables and initialises with their dimensionalities. It should always initialised with ccl_learn_model_pi_ws_alloc, and destroyed with ccl_learn_model_pi_ws_free.