Uses of Class
weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

Packages that use LocalScoreSearchAlgorithm

weka.classifiers.bayes.net.search.ci
weka.classifiers.bayes.net.search.local

Uses of LocalScoreSearchAlgorithm in weka.classifiers.bayes.net.search.ci

Subclasses of LocalScoreSearchAlgorithm in weka.classifiers.bayes.net.search.ci

class	CISearchAlgorithm The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
class	ICSSearchAlgorithm This Bayes Network learning algorithm uses conditional independence tests to find a skeleton, finds V-nodes and applies a set of rules to find the directions of the remaining arrows.

Uses of LocalScoreSearchAlgorithm in weka.classifiers.bayes.net.search.local

Subclasses of LocalScoreSearchAlgorithm in weka.classifiers.bayes.net.search.local

class	GeneticSearch This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.
class	HillClimber This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
class	K2 This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables. For more information see: G.F.
class	LAGDHillClimber This Bayes Network learning algorithm uses a Look Ahead Hill Climbing algorithm called LAGD Hill Climbing.
class	RepeatedHillClimber This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.
class	SimulatedAnnealing This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure. For more information see: R.R.
class	TabuSearch This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
class	TAN This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree. For more information see: N.