DATA604 hw3
population:
Statistics
A finite or infinite collection of items under consideration.
- Accuracy (all correct / all) = TP + TN / TP + TN + FP + FN
- Misclassification (all incorrect / all) = FP + FN / TP + TN + FP + FN
- Precision (true positives / predicted positives) = TP / TP + FP
- Sensitivity aka Recall (true positives / all actual positives) = TP / TP + FN
- Specificity (true negatives / all actual negatives) =TN / TN + FP
https://en.wikipedia.org/wiki/Sensitivity_and_specificity
- False positive rate (α) = type I error = 1 − specificity = FP / (FP + TN)
- False negative rate (β) = type II error = 1 − sensitivity = FN / (TP + FN)
https://towardsdatascience.com/baffling-concept-of-true-positive-and-true-negative-bffbc340f107
The average accuracy is calculated as the sum of the accuracy figures in column Accuracy divided by the number of classes in the test set.
The average reliability is calculated as the sum of the reliability figures in column Reliability divided by the number of classes in the test set.
The overall accuracy is calculated as the total number of correctly classified pixels (diagonal elements) divided by the total number of test pixels.