njab.sklearn.types module

njab.sklearn.types module#

class njab.sklearn.types.AucRocCurve(fpr, tpr, cutoffs)#

Bases: tuple

cutoffs#: Alias for field number 2

fpr#: Alias for field number 0

tpr#: Alias for field number 1

class njab.sklearn.types.PrecisionRecallCurve(precision, recall, cutoffs)#

Bases: tuple

cutoffs#: Alias for field number 2

precision#: Alias for field number 0

recall#: Alias for field number 1

class njab.sklearn.types.Results(model: BaseEstimator | None = None, selected_features: list | None = None, train: ResultsSplit | None = None, test: ResultsSplit | None = None, name: str | None = None)[source]#

Bases: object

Results for a model trained on a single split of train and test data.

model: BaseEstimator = None#

name: str = None#

selected_features: list = None#

test: ResultsSplit = None#

train: ResultsSplit = None#

class njab.sklearn.types.ResultsSplit(auc: float | None = None, aps: float | None = None, roc: AucRocCurve | None = None, prc: PrecisionRecallCurve | None = None)[source]#

Bases: object

Results for a single split of train and test data.

aps: float = None#

auc: float = None#

prc: PrecisionRecallCurve = None#

roc: AucRocCurve = None#

class njab.sklearn.types.Splits(X_train: DataFrame, X_test: DataFrame, y_train: Series, y_test: Series)[source]#

Bases: object

Splits of train and test data with targets.

X_test: DataFrame#

X_train: DataFrame#

y_test: Series#

y_train: Series#