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).