| Copyright | (c) Fabricio Olivetti de Franca 2020 |
|---|---|
| License | GPL-3 |
| Maintainer | fabricio.olivetti@gmail.com |
| Stability | experimental |
| Portability | POSIX |
| Safe Haskell | None |
IT.Metrics
Description
Definitions of support functions to calculate a set of error measures for regression and classification.
Synopsis
- type Vector = Vector Double
- data Measure = Measure {}
- mean :: Vector -> Double
- var :: Vector -> Double
- meanError :: (Vector -> Vector) -> Vector -> Vector -> Double
- mse :: Vector -> Vector -> Double
- mae :: Vector -> Vector -> Double
- nmse :: Vector -> Vector -> Double
- rmse :: Vector -> Vector -> Double
- rSq :: Vector -> Vector -> Double
- _rmse :: Measure
- _mae :: Measure
- _nmse :: Measure
- _r2 :: Measure
- _accuracy :: Measure
- _recall :: Measure
- _precision :: Measure
- _f1 :: Measure
- _logloss :: Measure
- accuracy :: Vector -> Vector -> Double
- precision :: Vector -> Vector -> Double
- recall :: Vector -> Vector -> Double
- f1 :: Vector -> Vector -> Double
- logloss :: Vector -> Vector -> Double
- measureAll :: [Measure]
- toMeasure :: String -> Measure
Documentation
Performance measures
Arguments
| :: (Vector -> Vector) | a function to be applied to the error terms (abs, square,...) |
| -> Vector | fitted values |
| -> Vector | target values |
| -> Double |
generic mean error measure
Common error measures for regression:
Regression measures
Classification measures
_precision :: Measure Source #
measureAll :: [Measure] Source #
List of all measures