A B C D E G I L M N P R S T

A

AbstractBayesianDistribution - Class in com.mapr.stats.random

Expresses the common characteristics of a two-level distribution in which the higher level distribution describes a prior distribution of parameters for the lower level distribution.

AbstractBayesianDistribution() - Constructor for class com.mapr.stats.random.AbstractBayesianDistribution

add(double) - Method in class com.mapr.stats.random.AbstractBayesianDistribution

add(double) - Method in class com.mapr.stats.random.BetaBinomialDistribution

add(double) - Method in class com.mapr.stats.random.GammaNormalDistribution

Adds an observed sample \(x\) to the distribution.

addModelDistribution(AbstractBayesianDistribution) - Method in class com.mapr.stats.bandit.BayesianBandit

addModelDistribution(AbstractBayesianDistribution) - Method in class com.mapr.stats.bandit.EpsilonGreedy

apply(double) - Method in class com.mapr.stats.bandit.ContextualBayesBandit.InverseLogisticFunction

apply(double) - Method in class com.mapr.stats.bandit.ContextualBayesBandit.LogisticFunction

averageRegret(String, int[], int, int) - Static method in class com.mapr.stats.bandit.BanditTrainer

Computes average regret relative to perfect knowledge given uniform random probabilities.

B

BanditFactory - Class in com.mapr.stats.bandit

Factory interface for creating bandit solvers.

BanditFactory() - Constructor for class com.mapr.stats.bandit.BanditFactory

BanditRanking - Class in com.mapr.bandit

Implements a Bandit ranking.

BanditRanking() - Constructor for class com.mapr.bandit.BanditRanking

BanditTrainer - Class in com.mapr.stats.bandit

Simulate a two-armed bandit playing against a beta-Bayesian model.

BanditTrainer() - Constructor for class com.mapr.stats.bandit.BanditTrainer

BayesianBandit - Class in com.mapr.stats.bandit

Implements the common characteristics of the Bayesian Bandit.

BayesianBandit() - Constructor for class com.mapr.stats.bandit.BayesianBandit

BetaBayesFactory - Class in com.mapr.stats.bandit

Factory that creates a BetaBayesModel for solving a multi-armed bandit with binary {0,1} rewards.

BetaBayesFactory() - Constructor for class com.mapr.stats.bandit.BetaBayesFactory

BetaBayesModel - Class in com.mapr.stats.bandit

Multi-armed bandit problem where each probability is modeled by a beta prior and data about positive and negative trials.

BetaBayesModel() - Constructor for class com.mapr.stats.bandit.BetaBayesModel

BetaBayesModel(int, Random) - Constructor for class com.mapr.stats.bandit.BetaBayesModel

BetaBinomialDistribution - Class in com.mapr.stats.random

Implements a beta-binomial pair of conjugate distributions.

BetaBinomialDistribution(double, double, Random) - Constructor for class com.mapr.stats.random.BetaBinomialDistribution

BetaDistribution - Class in com.mapr.stats.random

Sample from a beta distribution.

BetaDistribution(double, double, Random) - Constructor for class com.mapr.stats.random.BetaDistribution

BetaDistribution(double, double) - Constructor for class com.mapr.stats.random.BetaDistribution

BetaWalk - Class in com.mapr.stats

Follow a Metropolis random walk that should converge to a beta distribution.

BetaWalk(double, double, double) - Constructor for class com.mapr.stats.BetaWalk

BinomialDistributionSampler - Class in com.mapr.stats.random

BinomialDistributionSampler(double, double, Random) - Constructor for class com.mapr.stats.random.BinomialDistributionSampler

C

cdf(double) - Method in class com.mapr.stats.random.BetaDistribution

com.mapr.bandit - package com.mapr.bandit

com.mapr.stats - package com.mapr.stats

com.mapr.stats.bandit - package com.mapr.stats.bandit

com.mapr.stats.random - package com.mapr.stats.random

commitTime(String, int, double, double, int) - Static method in class com.mapr.stats.bandit.BanditTrainer

Records which bandit was chosen for many runs of the same scenario.

compareTo(DistributionWithMean) - Method in class com.mapr.stats.random.DistributionWithMean

ContextualBayesBandit - Class in com.mapr.stats.bandit

Solves the contextual bandit problem using Bayesian sampling.

ContextualBayesBandit(Matrix) - Constructor for class com.mapr.stats.bandit.ContextualBayesBandit

ContextualBayesBandit(Matrix, double, double) - Constructor for class com.mapr.stats.bandit.ContextualBayesBandit

ContextualBayesBandit.InverseLogisticFunction - Class in com.mapr.stats.bandit

ContextualBayesBandit.InverseLogisticFunction() - Constructor for class com.mapr.stats.bandit.ContextualBayesBandit.InverseLogisticFunction

ContextualBayesBandit.LogisticFunction - Class in com.mapr.stats.bandit

ContextualBayesBandit.LogisticFunction() - Constructor for class com.mapr.stats.bandit.ContextualBayesBandit.LogisticFunction

createBandit(int, Random) - Method in class com.mapr.stats.bandit.BanditFactory

createBandit(int, Random) - Method in class com.mapr.stats.bandit.BetaBayesFactory

createBandit(int, Random) - Method in class com.mapr.stats.bandit.EpsilonGreedyFactory

createBandit(int, Random) - Method in class com.mapr.stats.bandit.GammaNormalBayesFactory

D

DistributionGenerator - Class in com.mapr.stats.random

Generate a reference distribution for testing.

DistributionGenerator() - Constructor for class com.mapr.stats.random.DistributionGenerator

DistributionWithMean - Class in com.mapr.stats.random

Represents a distribution that knows it's own mean.

DistributionWithMean(AbstractContinousDistribution, double) - Constructor for class com.mapr.stats.random.DistributionWithMean

E

EpsilonGreedy - Class in com.mapr.stats.bandit

Solves a bandit problem using an epsilon greedy algorithm.

EpsilonGreedy(int, double, Random) - Constructor for class com.mapr.stats.bandit.EpsilonGreedy

EpsilonGreedyFactory - Class in com.mapr.stats.bandit

Factory that creates an epsilon greedy bandit solver.

EpsilonGreedyFactory(double) - Constructor for class com.mapr.stats.bandit.EpsilonGreedyFactory

G

GammaNormalBayesFactory - Class in com.mapr.stats.bandit

Factory that creates GammaNormalBayesModel objects with a standard call.

GammaNormalBayesFactory() - Constructor for class com.mapr.stats.bandit.GammaNormalBayesFactory

GammaNormalBayesModel - Class in com.mapr.stats.random

Multi-armed bandit problem where each reward is normally distributed with a gamma prior.

GammaNormalBayesModel(int, Random) - Constructor for class com.mapr.stats.random.GammaNormalBayesModel

GammaNormalDistribution - Class in com.mapr.stats.random

Samples from a Gamma-Normal distribution.

GammaNormalDistribution(double, double, double, Random) - Constructor for class com.mapr.stats.random.GammaNormalDistribution

getAlpha() - Method in class com.mapr.stats.random.BetaDistribution

getBeta() - Method in class com.mapr.stats.random.BetaDistribution

getMean(int) - Method in class com.mapr.stats.bandit.BayesianBandit

Returns the mean of a particular distribution in the bandit

getMean() - Method in class com.mapr.stats.random.AbstractBayesianDistribution

getMean() - Method in class com.mapr.stats.random.BetaBinomialDistribution

getMean() - Method in class com.mapr.stats.random.DistributionWithMean

getMean() - Method in class com.mapr.stats.random.GammaNormalDistribution

getSamples() - Method in class com.mapr.stats.random.AbstractBayesianDistribution

getSamples() - Method in class com.mapr.stats.random.BetaBinomialDistribution

getSamples() - Method in class com.mapr.stats.random.GammaNormalDistribution

I

iterator() - Method in class com.mapr.stats.bandit.BayesianBandit

Returns an iterator over a set of elements of type T.

L

logPdf(double) - Method in class com.mapr.stats.random.BetaDistribution

M

main(String[]) - Static method in class com.mapr.bandit.BanditRanking

main(String[]) - Static method in class com.mapr.stats.bandit.BanditTrainer

mean() - Method in class com.mapr.stats.random.BetaDistribution

N

nextDistribution() - Method in class com.mapr.stats.random.BinomialDistributionSampler

nextDistribution() - Method in class com.mapr.stats.random.DistributionGenerator

nextDistribution() - Method in class com.mapr.stats.random.NormalDistributionSampler

nextDouble() - Method in class com.mapr.stats.random.AbstractBayesianDistribution

nextDouble() - Method in class com.mapr.stats.random.BetaBinomialDistribution

Samples from a binomial whose underlying probability is distributed according to a beta distribution.

nextDouble() - Method in class com.mapr.stats.random.BetaDistribution

Returns a random number from the distribution.

nextDouble(double, double) - Method in class com.mapr.stats.random.BetaDistribution

nextDouble() - Method in class com.mapr.stats.random.DistributionWithMean

nextDouble() - Method in class com.mapr.stats.random.GammaNormalDistribution

Returns a random number from the distribution.

nextMean() - Method in class com.mapr.stats.random.AbstractBayesianDistribution

nextMean() - Method in class com.mapr.stats.random.BetaBinomialDistribution

nextMean() - Method in class com.mapr.stats.random.GammaNormalDistribution

nextSD() - Method in class com.mapr.stats.random.GammaNormalDistribution

NormalDistributionSampler - Class in com.mapr.stats.random

Returns a normal distribution whose mean is uniformly distributed on [0,1) and whose sd is as specified.

NormalDistributionSampler(double, Random) - Constructor for class com.mapr.stats.random.NormalDistributionSampler

P

pdf(double) - Method in class com.mapr.stats.random.BetaDistribution

posteriorDistribution() - Method in class com.mapr.stats.random.AbstractBayesianDistribution

posteriorDistribution() - Method in class com.mapr.stats.random.BetaBinomialDistribution

posteriorDistribution() - Method in class com.mapr.stats.random.GammaNormalDistribution

R

rank(int) - Method in class com.mapr.stats.bandit.BayesianBandit

Samples probability estimates from each bandit and orders the bandits in increasing order.

S

sample() - Method in class com.mapr.stats.bandit.BayesianBandit

Samples probability estimates from each bandit and picks the apparent best

sample() - Method in class com.mapr.stats.bandit.ContextualBayesBandit

sample() - Method in class com.mapr.stats.bandit.EpsilonGreedy

Samples probability estimates from each bandit and picks the apparent best

samplePi() - Method in class com.mapr.stats.bandit.ContextualBayesBandit

setAlpha(double) - Method in class com.mapr.stats.random.BetaDistribution

setBeta(double) - Method in class com.mapr.stats.random.BetaDistribution

setRandomGenerator(Random) - Method in class com.mapr.stats.random.BetaDistribution

Sets the uniform random generator internally used.

step() - Method in class com.mapr.stats.BetaWalk

T

totalRegret(String, String, int, int, int, BanditFactory, DistributionGenerator) - Static method in class com.mapr.stats.bandit.BanditTrainer

Computes average regret relative to perfect knowledge given uniform random probabilities.

train(int, double) - Method in class com.mapr.stats.bandit.BayesianBandit

Apply feedback to the bandit we chose.

train(int, boolean) - Method in class com.mapr.stats.bandit.ContextualBayesBandit

train(int, double) - Method in class com.mapr.stats.bandit.EpsilonGreedy

Apply feedback to the bandit we chose.

A B C D E G I L M N P R S T