HLearn-distributions-0.0.1.2: Distributions for use with the HLearn library

Safe HaskellNone

HLearn.Models.Distributions.Gaussian

Description

The Gaussian distribution is an instance of 'HomTrainer.' For examples of how to use this type, and the math behind it, see: http://izbicki.me/blog/gausian-distributions-are-monoids.

Synopsis

Documentation

data Gaussian datapoint Source

Constructors

Gaussian 

Fields

n :: !Int

The number of samples trained on

m1 :: !datapoint

The mean (first moment) of the trained distribution

m2 :: !datapoint

The variance (second moment) of the trained distribution times (n-1)

dc :: !Int

The number of "dummy points" that have been added to the distribution. Required for numerical stability reasons.

Instances

(MVector (Mutable Vector) (Gaussian a0), Unbox a0) => Vector Vector (Gaussian a0) 
Unbox a0 => MVector MVector (Gaussian a0) 
HomTrainer GaussianPDFParams (Gaussian Double) GaussianPDF 
Read datapoint => Read (Gaussian datapoint) 
Show datapoint => Show (Gaussian datapoint) 
NFData datapoint => NFData (Gaussian datapoint) 
Fractional datapoint => Semigroup (Gaussian datapoint) 
Fractional datapoint => Monoid (Gaussian datapoint) 
(Semigroup (Gaussian datapoint), Fractional datapoint) => RegularSemigroup (Gaussian datapoint) 
(RegularSemigroup (Gaussian datapoint), Monoid (Gaussian datapoint), Fractional datapoint) => Group (Gaussian datapoint) 
(Vector Vector (Gaussian a0), MVector MVector (Gaussian a0), Unbox a0) => Unbox (Gaussian a0) 
Distribution (Gaussian Double) Double Double 
HomTrainer (GaussianParams Double) Double (Gaussian Double) 
Model (GaussianParams datatype) (Gaussian datatype) 
Model (GaussianParams datatype) (Gaussian datatype) => DefaultModel (GaussianParams datatype) (Gaussian datatype) 

data GaussianParams datatype Source

Training a Gaussian distribution takes no parameters

Constructors

GaussianParams 

Instances