def __init__(self, raw_auc):
if raw_auc is None:
raise ValueError("Missing data for `raw_auc`.")
self.AUC = raw_auc["AUC"]
self.Gini = raw_auc["Gini"]
self.confusion_matrices = ConfusionMatrix.read_cms(
raw_auc["confusion_matrices"])
# Two Dim Table
self.thresholdsAndMetricScores = raw_auc["thresholdsAndMetricScores"]
self.maxCriteriaAndMetricScores = raw_auc["maxCriteriaAndMetricScores"]
def __init__(self, raw_auc=None):
if raw_auc is None:
raise ValueError("Missing data for `raw_auc`.")
self.actual_domain = raw_auc["actual_domain"]
self.AUC = raw_auc["AUC"]
self.Gini = raw_auc["Gini"]
self.confusion_matrices = CM.read_cms(raw_auc["confusion_matrices"])
self.F0point5 = raw_auc["F0point5"]
self.F1 = raw_auc["F1"]
self.F2 = raw_auc["F2"]
self.accuracy = raw_auc["accuracy"]
self.error = raw_auc["errorr"]
self.max_per_class_error = raw_auc["max_per_class_error"]
self.mcc = raw_auc["mcc"]
self.precision = raw_auc["precision"]
self.recall = raw_auc["recall"]
self.specificity = raw_auc["specificity"]
self.thresholds = raw_auc["thresholds"]
# the "for arrays" -- these are redundant
self.confusion_matrices_for_crit = \
CM.read_cms(raw_auc["confusion_matrix_for_criteria"])
self.F0point5_for_crit = raw_auc["F0point5_for_criteria"]
self.F1_for_crit = raw_auc["F1_for_criteria"]
self.F2_for_crit = raw_auc["F2_for_criteria"]
self.accuracy_for_crit = raw_auc["accuracy_for_criteria"]
self.error_for_crit = raw_auc["error_for_criteria"]
self.max_per_class_error_for_crit = raw_auc[
"max_per_class_error_for_criteria"]
self.mcc_for_crit = raw_auc["mcc_for_criteria"]
self.precision_for_crit = raw_auc["precision_for_criteria"]
self.recall_for_crit = raw_auc["recall_for_criteria"]
self.specificity_for_crit = raw_auc["specificity_for_criteria"]
self.thresholds_for_crit = raw_auc["threshold_for_criteria"]
c = ThresholdCriterion()
self.criteria = {
c.MAXF1: {
"threshold": self.thresholds_for_crit[0],
"value": self.F1_for_crit[0],
"cm": self.confusion_matrices_for_crit[0]
},
c.MAXF2: {
"threshold": self.thresholds_for_crit[1],
"value": self.F2_for_crit[1],
"cm": self.confusion_matrices_for_crit[1]
},
c.F0POINT5: {
"threshold": self.thresholds_for_crit[2],
"value": self.F0point5_for_crit[2],
"cm": self.confusion_matrices_for_crit[2]
},
c.ACCURACY: {
"threshold": self.thresholds_for_crit[3],
"value": self.accuracy_for_crit[3],
"cm": self.confusion_matrices_for_crit[3]
},
c.PRECISION: {
"threshold": self.thresholds_for_crit[4],
"value": self.precision_for_crit[4],
"cm": self.confusion_matrices_for_crit[4]
},
c.RECALL: {
"threshold": self.thresholds_for_crit[5],
"value": self.recall_for_crit[5],
"cm": self.confusion_matrices_for_crit[5]
},
c.SPECIFICITY: {
"threshold": self.thresholds_for_crit[6],
"value": self.specificity_for_crit[6],
"cm": self.confusion_matrices_for_crit[6]
},
c.MCC: {
"threshold": self.thresholds_for_crit[7],
"value": self.mcc_for_crit[7],
"cm": self.confusion_matrices_for_crit[7]
},
c.MINMAXPERCLASSERR: {
"threshold": self.thresholds_for_crit[8],
"value": self.max_per_class_error_for_crit[8],
"cm": self.confusion_matrices_for_crit[8]
}
}