Class LPM trains a linear classifier called Linear Programming Machine, i.e. a SVM using a norm regularizer.
It solves the following optimization problem using CPLEX:
Note that currently CPLEX is required to solve this problem. A faster implementation is available in CLPBoost.
Definition at line 43 of file LPM.h.
Public Member Functions | |
CLPM () | |
virtual | ~CLPM () |
virtual EClassifierType | get_classifier_type () |
virtual void | set_features (CDotFeatures *feat) |
void | set_C (float64_t c_neg, float64_t c_pos) |
float64_t | get_C1 () |
float64_t | get_C2 () |
void | set_bias_enabled (bool enable_bias) |
bool | get_bias_enabled () |
void | set_epsilon (float64_t eps) |
float64_t | get_epsilon () |
virtual const char * | get_name () const |
Protected Member Functions | |
virtual bool | train_machine (CFeatures *data=NULL) |
Protected Attributes | |
float64_t | C1 |
float64_t | C2 |
bool | use_bias |
float64_t | epsilon |
virtual EClassifierType get_classifier_type | ( | ) | [virtual] |
virtual const char* get_name | ( | void | ) | const [virtual] |
virtual void set_features | ( | CDotFeatures * | feat | ) | [virtual] |
bool train_machine | ( | CFeatures * | data = NULL |
) | [protected, virtual] |