21 using namespace shogun;
39 SG_ERROR(
"Specified features are not of type CDotFeatures\n")
47 ASSERT(num_vec==num_train_labels)
51 int32_t num_params=1+2*num_feat+num_vec;
53 memset(params,0,
sizeof(
float64_t)*num_params);
65 for (int32_t i=0; i<num_feat; i++)
66 w[i]=params[1+i]-params[1+num_feat+i];
70 CMath::display_vector(params,num_params,
"params");
72 CMath::display_vector(
w,w_dim,
"w");
73 CMath::display_vector(¶ms[1],w_dim,
"w+");
74 CMath::display_vector(¶ms[1+w_dim],w_dim,
"w-");
Class CCplex to encapsulate access to the commercial cplex general purpose optimizer.
bool init(E_PROB_TYPE t, int32_t timeout=60)
init cplex with problem type t and retry timeout 60 seconds
bool set_time_limit(float64_t seconds)
virtual int32_t get_num_labels() const =0
bool optimize(float64_t *sol, float64_t *lambda=NULL)
virtual int32_t get_num_vectors() const =0
virtual void set_features(CDotFeatures *feat)
Features that support dot products among other operations.
virtual int32_t get_dim_feature_space() const =0
static const float64_t epsilon
float64_t get_max_train_time()
virtual bool train_machine(CFeatures *data=NULL)
bool setup_lpm(float64_t C, CSparseFeatures< float64_t > *x, CBinaryLabels *y, bool use_bias)
Class LinearMachine is a generic interface for all kinds of linear machines like classifiers.
The class Features is the base class of all feature objects.
Binary Labels for binary classification.
virtual void set_bias(float64_t b)
bool has_property(EFeatureProperty p) const