Package org.nd4j.evaluation.classification

Evaluation metrics:
- precision, recall, f1, fBeta, accuracy, Matthews correlation coefficient, gMeasure
- Top N accuracy (if using constructor Evaluation.Evaluation(List, int))
- Custom binary evaluation decision threshold (use constructor Evaluation.Evaluation(double) (default if not set is argmax / 0.5)
- Custom cost array, using Evaluation.Evaluation(INDArray) or Evaluation.Evaluation(List, INDArray) for multi-class

Note: Care should be taken when using the Evaluation class for binary classification metrics such as F1, precision, recall, etc.

EvaluationCalibration is an evaluation class designed to analyze the calibration of a classifier.

ROC (Receiver Operating Characteristic) for multi-class classifiers.

AUROC: Area under ROC curve
AUPRC: Area under Precision-Recall Curve