Safe Haskell	None
Language	Haskell2010

DataFrame.Metrics.Report

Description

Bundled, pretty-printing evaluation summaries: a labelled confusion matrix and scikit-learn-style regression / classification reports. The *Expr variants take a model's prediction expression and a truth column directly, so a full report is a one-liner after fitting.

Synopsis

data ConfusionMatrix = ConfusionMatrix {
- cmClasses :: ![Double]
- cmCounts :: ![[Int]]
}
confusionMatrix :: Vector Double -> Vector Double -> ConfusionMatrix
confusionMatrixExpr :: Expr Double -> Expr Double -> DataFrame -> ConfusionMatrix
data RegressionReport = RegressionReport {
- rrMSE :: !Double
- rrRMSE :: !Double
- rrMAE :: !Double
- rrR2 :: !Double
}
regressionReport :: Vector Double -> Vector Double -> RegressionReport
regressionReportExpr :: Expr Double -> Expr Double -> DataFrame -> RegressionReport
data ClassStats = ClassStats {
- csPrecision :: !Double
- csRecall :: !Double
- csF1 :: !Double
- csSupport :: !Int
}
data ClassificationReport = ClassificationReport {
- crPerClass :: ![(Double, ClassStats)]
- crAccuracy :: !Double
- crMacroF1 :: !Double
- crWeightedF1 :: !Double
}
classificationReport :: Vector Double -> Vector Double -> ClassificationReport
classificationReportExpr :: Expr Double -> Expr Double -> DataFrame -> ClassificationReport

Documentation

data ConfusionMatrix Source #

A labelled confusion matrix: class order plus row-major actual×predicted.

Constructors

ConfusionMatrix
Fields cmClasses :: ![Double] cmCounts :: ![[Int]]

Instances

Instances details

Show ConfusionMatrix Source #
Instance details Defined in DataFrame.Metrics.Report Methods showsPrec :: Int -> ConfusionMatrix -> ShowS # show :: ConfusionMatrix -> String # showList :: [ConfusionMatrix] -> ShowS #
Eq ConfusionMatrix Source #
Instance details Defined in DataFrame.Metrics.Report Methods (==) :: ConfusionMatrix -> ConfusionMatrix -> Bool # (/=) :: ConfusionMatrix -> ConfusionMatrix -> Bool #

confusionMatrix :: Vector Double -> Vector Double -> ConfusionMatrix Source #

Confusion matrix over the class set of truth ∪ preds.

confusionMatrixExpr :: Expr Double -> Expr Double -> DataFrame -> ConfusionMatrix Source #

Confusion matrix from a prediction expression and a truth column.

data RegressionReport Source #

Regression metrics bundle.

Constructors

RegressionReport
Fields rrMSE :: !Double rrRMSE :: !Double rrMAE :: !Double rrR2 :: !Double

Instances

Instances details

Show RegressionReport Source #
Instance details Defined in DataFrame.Metrics.Report Methods showsPrec :: Int -> RegressionReport -> ShowS # show :: RegressionReport -> String # showList :: [RegressionReport] -> ShowS #
Eq RegressionReport Source #
Instance details Defined in DataFrame.Metrics.Report Methods (==) :: RegressionReport -> RegressionReport -> Bool # (/=) :: RegressionReport -> RegressionReport -> Bool #

regressionReport :: Vector Double -> Vector Double -> RegressionReport Source #

Regression report from prediction/truth vectors.

regressionReportExpr :: Expr Double -> Expr Double -> DataFrame -> RegressionReport Source #

Regression report from a prediction expression and a truth column.

data ClassStats Source #

Per-class precisionrecallF1/support.

Constructors

ClassStats
Fields csPrecision :: !Double csRecall :: !Double csF1 :: !Double csSupport :: !Int

Instances

Instances details

Show ClassStats Source #
Instance details Defined in DataFrame.Metrics.Report Methods showsPrec :: Int -> ClassStats -> ShowS # show :: ClassStats -> String # showList :: [ClassStats] -> ShowS #
Eq ClassStats Source #
Instance details Defined in DataFrame.Metrics.Report Methods (==) :: ClassStats -> ClassStats -> Bool # (/=) :: ClassStats -> ClassStats -> Bool #

data ClassificationReport Source #

A scikit-learn-style classification report: per-class stats plus accuracy and macro/weighted F1.

Constructors

ClassificationReport
Fields crPerClass :: ![(Double, ClassStats)] crAccuracy :: !Double crMacroF1 :: !Double crWeightedF1 :: !Double

Instances

Instances details

Show ClassificationReport Source #
Instance details Defined in DataFrame.Metrics.Report Methods showsPrec :: Int -> ClassificationReport -> ShowS # show :: ClassificationReport -> String # showList :: [ClassificationReport] -> ShowS #
Eq ClassificationReport Source #
Instance details Defined in DataFrame.Metrics.Report Methods (==) :: ClassificationReport -> ClassificationReport -> Bool # (/=) :: ClassificationReport -> ClassificationReport -> Bool #

classificationReport :: Vector Double -> Vector Double -> ClassificationReport Source #

Classification report from prediction/truth vectors.

classificationReportExpr :: Expr Double -> Expr Double -> DataFrame -> ClassificationReport Source #

Classification report from a prediction expression and a truth column.