evidently.metrics.regression_performance

Submodules

abs_perc_error_in_time module

class RegressionAbsPercentageErrorPlot()

Bases: Metric[RegressionAbsPercentageErrorPlotResults]

Methods:

calculate(data: InputData)

class RegressionAbsPercentageErrorPlotRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionAbsPercentageErrorPlot)

render_json(obj: RegressionAbsPercentageErrorPlot)

class RegressionAbsPercentageErrorPlotResults(current_scatter: Dict[str, pandas.core.series.Series], reference_scatter: Optional[Dict[str, pandas.core.series.Series]], x_name: str)

Bases: object

Attributes:

current_scatter : Dict[str, Series]

reference_scatter : Optional[Dict[str, Series]]

x_name : str

error_bias_table module

class RegressionErrorBiasTable(columns: Optional[List[str]] = None, top_error: Optional[float] = None)

Bases: Metric[RegressionErrorBiasTableResults]

Attributes:

TOP_ERROR_DEFAULT = 0.05

TOP_ERROR_MAX = 0.5

TOP_ERROR_MIN = 0

columns : Optional[List[str]]

top_error : float

Methods:

calculate(data: InputData)

class RegressionErrorBiasTableRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionErrorBiasTable)

render_json(obj: RegressionErrorBiasTable)

class RegressionErrorBiasTableResults(top_error: float, current_plot_data: pandas.core.frame.DataFrame, reference_plot_data: Optional[pandas.core.frame.DataFrame], target_name: str, prediction_name: str, num_feature_names: List[str], cat_feature_names: List[str], error_bias: Optional[dict] = None, columns: Optional[List[str]] = None)

Bases: object

Attributes:

cat_feature_names : List[str]

columns : Optional[List[str]] = None

current_plot_data : DataFrame

error_bias : Optional[dict] = None

num_feature_names : List[str]

prediction_name : str

reference_plot_data : Optional[DataFrame]

target_name : str

top_error : float

error_distribution module

class RegressionErrorDistribution()

Bases: Metric[RegressionErrorDistributionResults]

Methods:

calculate(data: InputData)

class RegressionErrorDistributionRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionErrorDistribution)

render_json(obj: RegressionErrorDistribution)

class RegressionErrorDistributionResults(current_bins: pandas.core.frame.DataFrame, reference_bins: Optional[pandas.core.frame.DataFrame])

Bases: object

Attributes:

current_bins : DataFrame

reference_bins : Optional[DataFrame]

error_in_time module

class RegressionErrorPlot()

Bases: Metric[RegressionErrorPlotResults]

Methods:

calculate(data: InputData)

class RegressionErrorPlotRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionErrorPlot)

render_json(obj: RegressionErrorPlot)

class RegressionErrorPlotResults(current_scatter: Dict[str, pandas.core.series.Series], reference_scatter: Optional[Dict[str, pandas.core.series.Series]], x_name: str)

Bases: object

Attributes:

current_scatter : Dict[str, Series]

reference_scatter : Optional[Dict[str, Series]]

x_name : str

error_normality module

class RegressionErrorNormality()

Bases: Metric[RegressionErrorNormalityResults]

Methods:

calculate(data: InputData)

class RegressionErrorNormalityRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionErrorNormality)

render_json(obj: RegressionErrorNormality)

class RegressionErrorNormalityResults(current_error: pandas.core.series.Series, reference_error: Optional[pandas.core.series.Series])

Bases: object

Attributes:

current_error : Series

reference_error : Optional[Series]

predicted_and_actual_in_time module

class RegressionPredictedVsActualPlot()

Bases: Metric[RegressionPredictedVsActualPlotResults]

Methods:

calculate(data: InputData)

class RegressionPredictedVsActualPlotRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionPredictedVsActualPlot)

render_json(obj: RegressionPredictedVsActualPlot)

class RegressionPredictedVsActualPlotResults(current_scatter: Dict[str, pandas.core.series.Series], reference_scatter: Optional[Dict[str, pandas.core.series.Series]], x_name: str)

Bases: object

Attributes:

current_scatter : Dict[str, Series]

reference_scatter : Optional[Dict[str, Series]]

x_name : str

predicted_vs_actual module

class RegressionPredictedVsActualScatter()

Bases: Metric[RegressionPredictedVsActualScatterResults]

Methods:

calculate(data: InputData)

class RegressionPredictedVsActualScatterRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionPredictedVsActualScatter)

render_json(obj: RegressionPredictedVsActualScatter)

class RegressionPredictedVsActualScatterResults(current_scatter: Dict[str, pandas.core.series.Series], reference_scatter: Optional[Dict[str, pandas.core.series.Series]])

Bases: object

Attributes:

current_scatter : Dict[str, Series]

reference_scatter : Optional[Dict[str, Series]]

regression_dummy_metric module

class RegressionDummyMetric()

Bases: Metric[RegressionDummyMetricResults]

Attributes:

quality_metric : RegressionQualityMetric

Methods:

calculate(data: InputData)

class RegressionDummyMetricRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionDummyMetric)

render_json(obj: RegressionDummyMetric)

class RegressionDummyMetricResults(rmse_default: float, mean_abs_error_default: float, mean_abs_perc_error_default: float, abs_error_max_default: float, mean_abs_error_by_ref: Optional[float] = None, mean_abs_error: Optional[float] = None, mean_abs_perc_error_by_ref: Optional[float] = None, mean_abs_perc_error: Optional[float] = None, rmse_by_ref: Optional[float] = None, rmse: Optional[float] = None, abs_error_max_by_ref: Optional[float] = None, abs_error_max: Optional[float] = None)

Bases: object

Attributes:

abs_error_max : Optional[float] = None

abs_error_max_by_ref : Optional[float] = None

abs_error_max_default : float

mean_abs_error : Optional[float] = None

mean_abs_error_by_ref : Optional[float] = None

mean_abs_error_default : float

mean_abs_perc_error : Optional[float] = None

mean_abs_perc_error_by_ref : Optional[float] = None

mean_abs_perc_error_default : float

rmse : Optional[float] = None

rmse_by_ref : Optional[float] = None

rmse_default : float

regression_performance_metrics module

class RegressionPerformanceMetrics()

Bases: Metric[RegressionPerformanceMetricsResults]

Methods:

calculate(data: InputData)

get_parameters()

class RegressionPerformanceMetricsRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionPerformanceMetrics)

render_json(obj: RegressionPerformanceMetrics)

class RegressionPerformanceMetricsResults(columns: DatasetColumns, r2_score: float, rmse: float, rmse_default: float, mean_error: float, me_default_sigma: float, me_hist_for_plot: Dict[str, Union[pandas.core.series.Series, pandas.core.frame.DataFrame]], mean_abs_error: float, mean_abs_error_default: float, mean_abs_perc_error: float, mean_abs_perc_error_default: float, abs_error_max: float, abs_error_max_default: float, error_std: float, abs_error_std: float, abs_perc_error_std: float, error_normality: dict, underperformance: dict, hist_for_plot: Dict[str, pandas.core.series.Series], vals_for_plots: Dict[str, Dict[str, pandas.core.series.Series]], error_bias: Optional[dict] = None, mean_error_ref: Optional[float] = None, mean_abs_error_ref: Optional[float] = None, mean_abs_perc_error_ref: Optional[float] = None, rmse_ref: Optional[float] = None, r2_score_ref: Optional[float] = None, abs_error_max_ref: Optional[float] = None, underperformance_ref: Optional[dict] = None)

Bases: object

Attributes:

abs_error_max : float

abs_error_max_default : float

abs_error_max_ref : Optional[float] = None

abs_error_std : float

abs_perc_error_std : float

columns : DatasetColumns

error_bias : Optional[dict] = None

error_normality : dict

error_std : float

hist_for_plot : Dict[str, Series]

me_default_sigma : float

me_hist_for_plot : Dict[str, Union[Series, DataFrame]]

mean_abs_error : float

mean_abs_error_default : float

mean_abs_error_ref : Optional[float] = None

mean_abs_perc_error : float

mean_abs_perc_error_default : float

mean_abs_perc_error_ref : Optional[float] = None

mean_error : float

mean_error_ref : Optional[float] = None

r2_score : float

r2_score_ref : Optional[float] = None

rmse : float

rmse_default : float

rmse_ref : Optional[float] = None

underperformance : dict

underperformance_ref : Optional[dict] = None

vals_for_plots : Dict[str, Dict[str, Series]]

regression_quality module

class RegressionQualityMetric()

Bases: Metric[RegressionQualityMetricResults]

Methods:

calculate(data: InputData)

class RegressionQualityMetricRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionQualityMetric)

render_json(obj: RegressionQualityMetric)

class RegressionQualityMetricResults(columns: DatasetColumns, r2_score: float, rmse: float, rmse_default: float, mean_error: float, me_default_sigma: float, me_hist_for_plot: Dict[str, pandas.core.series.Series], mean_abs_error: float, mean_abs_error_default: float, mean_abs_perc_error: float, mean_abs_perc_error_default: float, abs_error_max: float, abs_error_max_default: float, error_std: float, abs_error_std: float, abs_perc_error_std: float, error_normality: dict, underperformance: dict, hist_for_plot: Dict[str, pandas.core.series.Series], vals_for_plots: Dict[str, Dict[str, pandas.core.series.Series]], error_bias: Optional[dict] = None, mean_error_ref: Optional[float] = None, mean_abs_error_ref: Optional[float] = None, mean_abs_perc_error_ref: Optional[float] = None, rmse_ref: Optional[float] = None, r2_score_ref: Optional[float] = None, abs_error_max_ref: Optional[float] = None, underperformance_ref: Optional[dict] = None, error_std_ref: Optional[float] = None, abs_error_std_ref: Optional[float] = None, abs_perc_error_std_ref: Optional[float] = None)

Bases: object

Attributes:

abs_error_max : float

abs_error_max_default : float

abs_error_max_ref : Optional[float] = None

abs_error_std : float

abs_error_std_ref : Optional[float] = None

abs_perc_error_std : float

abs_perc_error_std_ref : Optional[float] = None

columns : DatasetColumns

error_bias : Optional[dict] = None

error_normality : dict

error_std : float

error_std_ref : Optional[float] = None

hist_for_plot : Dict[str, Series]

me_default_sigma : float

me_hist_for_plot : Dict[str, Series]

mean_abs_error : float

mean_abs_error_default : float

mean_abs_error_ref : Optional[float] = None

mean_abs_perc_error : float

mean_abs_perc_error_default : float

mean_abs_perc_error_ref : Optional[float] = None

mean_error : float

mean_error_ref : Optional[float] = None

r2_score : float

r2_score_ref : Optional[float] = None

rmse : float

rmse_default : float

rmse_ref : Optional[float] = None

underperformance : dict

underperformance_ref : Optional[dict] = None

vals_for_plots : Dict[str, Dict[str, Series]]

top_error module

class RegressionTopErrorMetric()

Bases: Metric[RegressionTopErrorMetricResults]

Methods:

calculate(data: InputData)

class RegressionTopErrorMetricRenderer(color_options: Optional[ColorOptions] = None)

Bases: MetricRenderer

Attributes:

color_options : ColorOptions

Methods:

render_html(obj: RegressionTopErrorMetric)

render_json(obj: RegressionTopErrorMetric)

class RegressionTopErrorMetricResults(curr_mean_err_per_group: Dict[str, Dict[str, float]], curr_scatter: Dict[str, Dict[str, pandas.core.series.Series]], ref_mean_err_per_group: Optional[Dict[str, Dict[str, float]]], ref_scatter: Optional[Dict[str, Dict[str, pandas.core.series.Series]]])

Bases: object

Attributes:

curr_mean_err_per_group : Dict[str, Dict[str, float]]

curr_scatter : Dict[str, Dict[str, Series]]

ref_mean_err_per_group : Optional[Dict[str, Dict[str, float]]]

ref_scatter : Optional[Dict[str, Dict[str, Series]]]