A C D E F G H I L M N P Q R S T V W

A

add(int, int) - Method in class gmm.DirectedGraph

Adds the specified edge to the graph, and others that might be needed to maintain transitive closure.

AStar - Class in gmm

This class implements the A* search for finding the maximum likelihood parameters for GMM.

AStar(boolean, float[][], int, int) - Constructor for class gmm.AStar

C

compareTo(ItemRank) - Method in class gmm.ItemRank

compareTo(Node) - Method in class gmm.Node

computeLogL() - Method in class gmm.GMMEstimator

Must be called by a subclass only after the theta values have been set.

computeThetas() - Method in class gmm.GMMEstimator

Sets the theta values.

computeVjs() - Method in class gmm.GMMEstimator

Sets the V_j values.

D

DirectedGraph - Class in gmm

DirectedGraph(int) - Constructor for class gmm.DirectedGraph

Creates an empty graph with the specified number of nodes.

displayMatrixQ(float[][]) - Method in class gmm.InputGenerator

E

ExptsManager - Class in gmm

ExptsManager() - Constructor for class gmm.ExptsManager

F

finishedWithBeam() - Method in class gmm.AStar

freeMemory() - Static method in class gmm.ExptsManager

FVHeuristic - Class in gmm

This class implements the GMM estimator based on the Fligner-Verducci heuristic described in "Multistage Ranking Models".

FVHeuristic(boolean, float[][]) - Constructor for class gmm.FVHeuristic

G

generateRanking(int[]) - Method in class gmm.InputGenerator

generatesQFromModel() - Method in class gmm.InputGenerator

generateVj(int) - Method in class gmm.InputGenerator

get_n() - Method in class gmm.InputGenerator

getAvgDk() - Method in class gmm.GMMEstimator

getDistance(int[], int[]) - Static method in class gmm.ExptsManager

getHeuristicValue(Node, GMMEstimator) - Method in class gmm.HeuristicComputer

getLocalSearchSteps() - Method in class gmm.FVHeuristic

getLogL() - Method in class gmm.GMMEstimator

getLogLForQ(float[][]) - Method in class gmm.GMMEstimator

getMatrixQ() - Method in class gmm.InputGenerator

getMinCliqueWeights() - Method in class gmm.HeuristicComputer

getN() - Method in class gmm.InputGenerator

getNodesGenerated() - Method in class gmm.AStar

getNodesGeneratedAsMultiple() - Method in class gmm.AStar

getPi() - Method in class gmm.GMMEstimator

getRunningTime() - Method in class gmm.GMMEstimator

getStdDev(float, float, int) - Static method in class gmm.ExptsManager

getTopologicalSort() - Method in class gmm.DirectedGraph

Assumes that an edge exists between any pair of nodes i and j.

gmm - package gmm

GMM - Variable in class gmm.GMMEstimator

GMMEstimator - Class in gmm

This abstract class represents a estimator of the Generalized Mallows Model.

GMMEstimator(boolean, float[][]) - Constructor for class gmm.GMMEstimator

GreedyCSS - Class in gmm

This class implements the GMM estimator based on the greedy search algorithm of Cohen, Schapire and Singer.

GreedyCSS(boolean, float[][]) - Constructor for class gmm.GreedyCSS

GreedyDK - Class in gmm

This class implements the Mallows Model estimator based on the greedy algorithm of Davenport and Kalagnanam for finding the modal ranking (the consensus ranking).

GreedyDK(boolean, float[][]) - Constructor for class gmm.GreedyDK

H

HeuristicComputer - Class in gmm

HeuristicComputer(float[][]) - Constructor for class gmm.HeuristicComputer

I

InputGenerator - Class in gmm

This class generates instances of the input matrix Q.

InputGenerator(String) - Constructor for class gmm.InputGenerator

isGMM() - Method in class gmm.InputGenerator

ItemRank - Class in gmm

ItemRank() - Constructor for class gmm.ItemRank

L

lnPsiJPrime(int, float) - Method in class gmm.GMMEstimator

logL - Variable in class gmm.GMMEstimator

M

main(String[]) - Static method in class gmm.ExptsManager

main(String[]) - Static method in class gmm.InputGenerator

main(String[]) - Static method in class gmm.Node

maxIters - Static variable in class gmm.GMMEstimator

minimizeF(float) - Method in class gmm.GMMEstimator

minimizeFj(int, float) - Method in class gmm.GMMEstimator

minValueOfFj(int, float) - Method in class gmm.GMMEstimator

N

n - Variable in class gmm.GMMEstimator

Node - Class in gmm

This class represents a node in the search tree being explored by the A* search algorithm.

Node() - Constructor for class gmm.Node

NodeCSS - Class in gmm

This class represents a node in the search tree being explored by the greedy CSS algorithm.

NodeCSS() - Constructor for class gmm.NodeCSS

P

pi - Variable in class gmm.GMMEstimator

printLearnedModel(PrintWriter) - Method in class gmm.GMMEstimator

PsiJ(int, float) - Method in class gmm.GMMEstimator

Q

Q - Variable in class gmm.GMMEstimator

R

R - Static variable in class gmm.HeuristicComputer

RandomEstimator - Class in gmm

This class implements a random GMM estimator.

RandomEstimator(boolean, float[][]) - Constructor for class gmm.RandomEstimator

run() - Method in class gmm.AStar

run() - Method in class gmm.FVHeuristic

run() - Method in class gmm.GMMEstimator

This method causes the estimator to run, and estimate the GMM parameters.

run() - Method in class gmm.GreedyCSS

run() - Method in class gmm.GreedyDK

run() - Method in class gmm.RandomEstimator

runningTime - Variable in class gmm.GMMEstimator

runtime - Static variable in class gmm.ExptsManager

S

size - Static variable in class gmm.Node

sumOfLnPsiJPrime(int, int, float) - Method in class gmm.GMMEstimator

T

theta - Variable in class gmm.GMMEstimator

V

V - Variable in class gmm.GMMEstimator

W

W - Static variable in class gmm.HeuristicComputer

A C D E F G H I L M N P Q R S T V W