Uses of Class
gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry

Packages that use SuccessiveOverrelaxation.Entry
gov.sandia.cognition.learning.algorithm.svm Provides implementations of Support Vector Machine (SVM) learning algorithms. 
 

Uses of SuccessiveOverrelaxation.Entry in gov.sandia.cognition.learning.algorithm.svm
 

Fields in gov.sandia.cognition.learning.algorithm.svm with type parameters of type SuccessiveOverrelaxation.Entry
protected  ArrayList<SuccessiveOverrelaxation.Entry> SuccessiveOverrelaxation.entries
          The entry information that the algorithm keeps.
protected  LinkedHashMap<InputOutputPair<? extends InputType,? extends Boolean>,SuccessiveOverrelaxation.Entry> SuccessiveOverrelaxation.supportsMap
          The mapping of weight objects to non-zero weighted examples (support vectors).
 

Methods in gov.sandia.cognition.learning.algorithm.svm that return types with arguments of type SuccessiveOverrelaxation.Entry
protected  ArrayList<SuccessiveOverrelaxation.Entry> SuccessiveOverrelaxation.getEntries()
          Gets the data that the algorithm keeps for each training instance.
protected  LinkedHashMap<InputOutputPair<? extends InputType,? extends Boolean>,SuccessiveOverrelaxation.Entry> SuccessiveOverrelaxation.getSupportsMap()
          Gets the mapping of examples to weight objects (support vectors).
 

Methods in gov.sandia.cognition.learning.algorithm.svm with parameters of type SuccessiveOverrelaxation.Entry
 int SuccessiveOverrelaxation.Entry.compareTo(SuccessiveOverrelaxation.Entry other)
          Compares this entry to another one by comparing the weights.
protected  void SuccessiveOverrelaxation.update(SuccessiveOverrelaxation.Entry entry)
          Performs an update step on the given entry using the successive overrelaxation procedure.
 

Method parameters in gov.sandia.cognition.learning.algorithm.svm with type arguments of type SuccessiveOverrelaxation.Entry
protected  void SuccessiveOverrelaxation.setEntries(ArrayList<SuccessiveOverrelaxation.Entry> entries)
          Gets the data that the algorithm keeps for each training instance.
protected  void SuccessiveOverrelaxation.setSupportsMap(LinkedHashMap<InputOutputPair<? extends InputType,? extends Boolean>,SuccessiveOverrelaxation.Entry> supportsMap)
          Gets the mapping of examples to weight objects (support vectors).