11 #ifndef CONDITIONALPROBABILITYTREE_H__
12 #define CONDITIONALPROBABILITYTREE_H__
52 virtual const char*
get_name()
const {
return "VwConditionalProbabilityTree"; }
float64_t train_node(VwExample *ex, node_t *node)
virtual bool which_subtree(node_t *node, VwExample *ex)=0
void train_example(VwExample *ex)
virtual bool train_require_labels() const
float64_t accumulate_conditional_probability(node_t *leaf)
VwConditionalProbabilityTreeNodeData()
int32_t m_num_passes
number of passes for online training
Multiclass Labels for multi-class classification.
int32_t get_num_passes() const
std::map< int32_t, node_t * > m_leaves
class => leaf mapping
CTreeMachineNode< VwConditionalProbabilityTreeNodeData > node_t
virtual bool train_machine(CFeatures *data)
virtual CMulticlassLabels * apply_multiclass(CFeatures *data=NULL)
void set_features(CStreamingVwFeatures *feats)
void set_num_passes(int32_t num_passes)
int32_t create_machine(VwExample *ex)
This class implements streaming features for use with VW.
all of classes and functions are contained in the shogun namespace
CVwConditionalProbabilityTree(int32_t num_passes=1)
The class Features is the base class of all feature objects.
virtual const char * get_name() const
void train_path(VwExample *ex, node_t *node)
virtual int32_t apply_multiclass_example(VwExample *ex)
virtual ~CVwConditionalProbabilityTree()
CStreamingVwFeatures * m_feats
online features
class TreeMachine, a base class for tree based multiclass classifiers
void compute_conditional_probabilities(VwExample *ex)