# ---------------------------------------------------------------------
# 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'],