29 #ifndef GRT_DECISION_STUMP_HEADER
30 #define GRT_DECISION_STUMP_HEADER
86 virtual double predict(
const VectorDouble &x);
107 virtual void print()
const;
139 #endif //GRT_DECISION_STUMP_HEADER
UINT numRandomSplits
The number of random splits used to search for the best decision spilt.
UINT getNumRandomSplits() const
DecisionStump & operator=(const DecisionStump &rhs)
virtual void print() const
virtual bool saveModelToFile(fstream &file) const
static RegisterWeakClassifierModule< DecisionStump > registerModule
This is used to register the DecisionStump with the WeakClassifier base class.
virtual double predict(const VectorDouble &x)
This is the main base class for all GRT WeakClassifiers.
DecisionStump(const UINT numRandomSplits=100)
UINT decisionFeatureIndex
The dimension that the data will be spilt on.
virtual bool train(ClassificationData &trainingData, VectorDouble &weights)
UINT getDirection() const
UINT getDecisionFeatureIndex() const
UINT direction
Indicates if the decision spilt threshold is greater than (1), or less than (0)
virtual bool loadModelFromFile(fstream &file)
virtual bool deepCopyFrom(const WeakClassifier *weakClassifer)
double decisionValue
The decision spilt threshold.
double getDecisionValue() const