binary_classification_debriefing

hana_ml.algorithms.pal.metrics.binary_classification_debriefing(data, label_true, label_pred, auc_data=None, positive_label=1, negative_label=0)

Computes debriefing coefficients for binary classification results.

Parameters:

dataDataFrame

DataFrame of true and predicted values.

label_truestr

Name of the column containing true values.

label_predstr

Name of the column containing values predicted by regression.

auc_dataDataFrame, optional

Input data for calculating predictive power(KI), structured as follows:

• ID column.

• True class of the data point.

• Classifier-computed probability that the data point belongs to the positive class.

positive_labelstr or int, optional

Positive label for binary classification.

Defaults to 1.

negative_labelstr or int, optional

Negative label for binary classification.

Defaults to 0.

Returns:

dict

Debriefing stats: ACCURACY, RECALL, SPECIFICITY, PRECISION, FPR, FNR, F1, MCC, KI, KAPPA, SELECTION RATE.