from evidently.dashboard import Dashboard
        from evidently.pipeline.column_mapping import ColumnMapping
        from evidently.tabs import CatTargetDriftTab, DataDriftTab

        column_mapping = ColumnMapping()
        column_mapping.target = target
        column_mapping.prediction = None
        column_mapping.datetime = None
        column_mapping.numerical_features = numeric_features
        column_mapping.categorical_features = categorical_features
        column_mapping.datetime_features = date_features

        if target not in reference_data.columns or target not in current_data.columns:
            raise ValueError(
                f"Both dataset must contain a label column {target} "
                "in order to create a drift report."
            )

        dashboard = Dashboard(tabs=[DataDriftTab(), CatTargetDriftTab()])
        dashboard.calculate(reference_data, current_data, column_mapping=column_mapping)
        filename = (
            filename or f"{self.exp_name_log}_{int(time.time())}_Drift_Report.html"
        )
        dashboard.save(filename)
        return filename

        from evidently import ColumnMapping
        from evidently.metric_preset import DataDriftPreset, TargetDriftPreset
        from evidently.report import Report

        column_mapping = ColumnMapping()
        column_mapping.target = target
        column_mapping.prediction = None
        column_mapping.datetime = None
        column_mapping.numerical_features = numeric_features
        column_mapping.categorical_features = categorical_features
        column_mapping.datetime_features = date_features

        report = Report(metrics=[DataDriftPreset(), TargetDriftPreset()])

        # Generate the report filename
        filename = f"{self.exp_name_log}_{int(time.time())}_Drift_Report.html"

        # Save the report as an HTML file
        report.save(filename)

        # Return the filename
        return filename