Machine Learning, Probability, Statistics, Data Science, Deep Learning.
such. False Positives (FP): number of negative examples, labeled as positive. True Negatives (TN): number of negative examples, labeled as such. False Negatives (FN): number of positive examples, labeled as negative. Accuracy = (TP + TN)/(TP + FP + TN + FN) Confusion matrix: It is a matrix