| Copyright | (c) Alexander Ignatyev 2016 |
|---|---|
| License | BSD-3 |
| Stability | experimental |
| Portability | POSIX |
| Safe Haskell | None |
| Language | Haskell2010 |
MachineLearning.LogisticModel
Description
Synopsis
- module MachineLearning.Model
- data LogisticModel = Logistic
- sigmoid :: Floating a => a -> a
- sigmoidGradient :: Floating a => a -> a
Documentation
module MachineLearning.Model
data LogisticModel #
Constructors
| Logistic |
Instances
| Model LogisticModel # | |
Defined in MachineLearning.LogisticModel Methods hypothesis :: LogisticModel -> Matrix -> Vector -> Vector # cost :: LogisticModel -> Regularization -> Matrix -> Vector -> Vector -> R # gradient :: LogisticModel -> Regularization -> Matrix -> Vector -> Vector -> Vector # | |
sigmoidGradient :: Floating a => a -> a #
Calculates derivatives of sigmoid