Hopfield.Clusters

Documentation

getPatternInCluster :: MonadRandom m => Method -> Pattern -> Double -> m Pattern

getPatternInCluster pat p gets a pattern in a cluster given by pat by flipping each bit in the pattern with probability p.

getCluster :: MonadRandom m => Method -> Pattern -> Int -> Double -> m [Pattern]

getPatternInCluster pat p gets a pattern in a cluster given by pat by flipping each bit in the pattern with probability p.

getGaussianCluster :: MonadRandom m => Method -> Pattern -> Int -> Double -> Double -> m [Pattern]

basinsGivenProbabilityT1 :: MonadRandom m => LearningType -> Int -> Int -> Double -> m Double

basinsGivenProbabilityT1 learning networkSize clusterSize p Gets the average basin of attraction of a cluster of size clusterSize constructed using the T1 method given the flip probability p. A hopfield network is trained (the type of training (Hebbian or Storkey) is given by learning).

experimentUsingT1 :: MonadRandom m => LearningType -> Int -> Int -> m Double

experimentUsingT1 learning networkSize clusterSize Gets the average basin of attraction obtained by iterating trough various probabilities for flipping the bit when obtaining the cluster.

experimentUsingT1NoAvg :: MonadRandom m => LearningType -> Int -> Int -> m [(Double, Double)]

basinsGivenProbabilityT1With2Clusters :: MonadRandom m => LearningType -> Int -> Int -> Double -> Double -> m (Double, Double)

basinsGivenStdT2 :: MonadRandom m => LearningType -> Int -> Int -> Double -> Double -> m Double

experimentUsingT2 :: MonadRandom m => LearningType -> Int -> Int -> m Double

experimentUsingT2NoAvg :: MonadRandom m => LearningType -> Int -> Int -> m [(Double, Double)]

basinsGivenStdT2With2Clusters :: MonadRandom m => LearningType -> Int -> Int -> Double -> Double -> Double -> Double -> m (Double, Double)

avgBasinsGivenPats :: MonadRandom m => LearningType -> [Pattern] -> m Double

repeatExperiment :: MonadRandom m => (LearningType -> Int -> Int -> m Double) -> LearningType -> Int -> Int -> Int -> m Double