code: def on_predict(self, data):
      try:
          if self._dataframeColumns is not None:
              data = pd.DataFrame(data, columns=self._dataframeColumns)
              data = data.astype(dict(self._dfdtypes))
          if self._is_classifier:
              model_pred_proba = self._model.predict_proba(data)
              prediction = convert_to_list(model_pred_proba)
          else:
              model_predict = self._model.predict(data)
              prediction = convert_to_list(model_predict)
          return {WidgetRequestResponseConstants.DATA: prediction}
      except Exception:
          return {
              WidgetRequestResponseConstants.ERROR: "Model threw exception while predicting...",
              WidgetRequestResponseConstants.DATA: [],
          }
  
imports: import traceback
  import numpy
  import pandas
  from erroranalysis._internal.constants import Metrics, display_name_to_metric, metric_to_display_name
  from erroranalysis._internal.error_analyzer import ModelAnalyzer, PredictionsAnalyzer
  from erroranalysis._internal.utils import is_spark
  from raiutils.data_processing import convert_to_list, serialize_json_safe
  from raiutils.models import is_classifier
  from responsibleai._interfaces import ErrorAnalysisData
  from .constants import ModelTask
  from .error_analysis_constants import ErrorAnalysisDashboardInterface, MethodConstants
  from .error_handling import _format_exception
  from .explanation_constants import ExplanationDashboardInterface, WidgetRequestResponseConstants
label_desc: Use image node_id 13 for calling the ErrorAnalysisDashboardInput obj's underlying member method code with example usage: obj.on_predict(data) and returns: dict, dict