iguanas.metrics.classification.FScore

class iguanas.metrics.classification.FScore(beta: float)[source]

Calculates the Fbeta score for either a single or set of binary predictors.

Parameters
betafloat

The beta value used to calculate the Fbeta score.

fit(y_true: Union[iguanas.utils.typing.numpy.ndarray, iguanas.utils.typing.pandas.core.series.Series, iguanas.utils.typing.databricks.koalas.series.Series], y_preds: Union[iguanas.utils.typing.numpy.ndarray, iguanas.utils.typing.pandas.core.series.Series, iguanas.utils.typing.databricks.koalas.series.Series, iguanas.utils.typing.pandas.core.frame.DataFrame, iguanas.utils.typing.databricks.koalas.frame.DataFrame], sample_weight=None) Union[float, iguanas.utils.typing.numpy.ndarray][source]

Calculates the Fbeta score for either a single or set of binary predictors.

Parameters
y_trueUnion[NumpyArrayType, PandasSeriesType, KoalasSeriesType]

The target column.

y_predsUnion[NumpyArrayType, PandasSeriesType, KoalasSeriesType, PandasDataFrameType, KoalasDataFrameType]

The binary predictor column(s).

sample_weightUnion[NumpyArrayType, PandasSeriesType, KoalasSeriesType], optional

Row-wise weights to apply. Defaults to None.

Returns
Union[float, NumpyArrayType]

The Fbeta score(s).