70 for (int32_t i=0; i<y.vlen; i++)
73 malsar_options options = malsar_options::default_options();
78 options.tasks_indices = tasks;
89 SG_WARNING(
"Clustered LR is unstable with C++11\n")
94 SG_WARNING(
"Please install Eigen3 to use MultitaskClusteredLogisticRegression\n")
111 for (int32_t i=0; i<y.vlen; i++)
114 malsar_options options = malsar_options::default_options();
130 SG_WARNING(
"Clustered LR is unstable with C++11\n")
135 SG_WARNING(
"Please install Eigen3 to use MultitaskClusteredLogisticRegression\n")
140 SG_FREE(options.tasks_indices);
CMultitaskClusteredLogisticRegression()
int32_t get_num_clusters() const
virtual int32_t get_num_labels() const =0
void set_num_clusters(int32_t num_clusters)
void set_rho1(float64_t rho1)
class TaskGroup used to represent a group of tasks. Tasks in group do not overlap.
Features that support dot products among other operations.
class Multitask Logistic Regression used to solve classification problems with a few tasks related vi...
virtual bool train_machine(CFeatures *data=NULL)
CTaskRelation * m_task_relation
void set_rho2(float64_t rho2)
virtual void set_features(CDotFeatures *feat)
SGMatrix< float64_t > m_tasks_w
virtual bool train_locked_implementation(SGVector< index_t > *tasks)
malsar_result_t malsar_clustered(CDotFeatures *features, double *y, double rho1, double rho2, const malsar_options &options)
The class Features is the base class of all feature objects.
Binary Labels for binary classification.
SGVector< float64_t > m_tasks_c
used to represent tasks in multitask learning
virtual ~CMultitaskClusteredLogisticRegression()