HLearn.Models.Distributions.Univariate.Categorical

The categorical distribution is used for discrete data. It is also sometimes called the discrete distribution or the multinomial distribution. For more, see the wikipedia entry: https://en.wikipedia.org/wiki/Categorical_distribution

Data types

data Categorical sampletype prob

Constructors

Categorical !(Map sampletype prob)

Instances

(Eq sampletype, Eq prob) => Eq (Categorical sampletype prob)

(Ord sampletype, Ord prob) => Ord (Categorical sampletype prob)

(Ord sampletype, Read sampletype, Read prob) => Read (Categorical sampletype prob)

(Show sampletype, Show prob) => Show (Categorical sampletype prob)

(Ord label, Num prob) => Monoid (Categorical label prob)

Num prob => NumDP (Categorical label prob)

(Ord label, Num prob) => HomTrainer (Categorical label prob)

Num prob => HasRing (Categorical label prob)

(Ord label, Num prob) => Module (Categorical label prob)

(Ord label, Num prob) => Abelian (Categorical label prob)

(Ord label, Num prob) => Group (Categorical label prob)

(NFData sampletype, NFData prob) => NFData (Categorical sampletype prob)

(Num prob, Ord prob, Ord label) => Mean (Categorical label prob)

(Ord label, Ord prob, Fractional prob) => PDF (Categorical label prob)

(Ord label, Ord prob, Fractional prob) => CDF (Categorical label prob)

Probabilistic (Categorical label prob)

(Ord label, Show label, Ord prob, Show prob, Fractional prob) => PlottableDistribution (Categorical label prob)

Helper functions

dist2list :: Categorical sampletype prob -> [(sampletype, prob)]

Converts a distribution into a list of (sample,probability) pai

mostLikely :: Ord prob => Categorical label prob -> label

Extracts the element in the distribution with the highest probability