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

newtype Categorical prob label

Constructors

Categorical (Map label prob)

Instances

(Num prob, Ord prob) => Monad (Categorical prob)

Functor (Categorical prob)

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

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

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

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

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

Num prob => NumDP (Categorical prob label)

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

Num prob => HasRing (Categorical prob label)

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

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

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

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

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

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

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

Probabilistic (Categorical prob label)

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

Helper functions

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

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

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

Extracts the element in the distribution with the highest probability