# --------------------------------------------------------------------- # EVALUATE THE MODEL # --------------------------------------------------------------------- evaluationConfiguration = { 'distance': 1, 'hypo': 1, 'clarke': 1, 'lag': 1, 'plotLag': 1, 'plotTimeseries': 1 } # --------------------------------------------------------------------- # Define evaluation class evalObject = evaluateModel(data_obj_hyperOpt, model) if evaluationConfiguration['distance']: distance = evalObject.get_distanceAnalysis() if evaluationConfiguration['hypo']: hypo = evalObject.get_hypoAnalysis() if evaluationConfiguration['lag']: lag = evalObject.get_lagAnalysis(figure_path=model_figure_path) if evaluationConfiguration['plotTimeseries']: evalObject.get_timeSeriesPlot(figure_path=model_figure_path) if evaluationConfiguration['clarke']: clarkes, clarkes_prob = evalObject.clarkesErrorGrid( 'mg/dl', figure_path=model_figure_path) scores.loc[str([train_data, test_data])] = [ distance['rmse'], distance['mard'], distance['mae'], clarkes_prob['A'],
# --------------------------------------------------------------------- # EVALUATE THE MODEL # --------------------------------------------------------------------- evaluationConfiguration = { 'distance': 1, 'hypo': 1, 'clarke': 1, 'lag': 0, 'plotLag': 0, 'plotTimeseries': 0 } # --------------------------------------------------------------------- # Define evaluation class evalObject = evaluateModel(data_obj, model) if evaluationConfiguration['distance']: distance = evalObject.get_distanceAnalysis() if evaluationConfiguration['hypo']: hypo = evalObject.get_hypoAnalysis() if evaluationConfiguration['lag']: lag = evalObject.get_lagAnalysis(figure_path=model_figure_path) if evaluationConfiguration['plotTimeseries']: evalObject.get_timeSeriesPlot(figure_path=model_figure_path) if evaluationConfiguration['clarke']: clarkes, clarkes_prob = evalObject.clarkesErrorGrid( 'mg/dl', figure_path=model_figure_path) scores.loc[str([test_data])] = [ distance['rmse'], distance['mard'], distance['mae'], clarkes_prob['A'],