3.8.1. Precision

It is the proportion of correct positive predictions to the total positive prediction. It indicates the rate of correct positive predictions. It is calculated as:

$$Precision = \frac{TP}{(TP + FP)} \times 100\tag{5}$$

#### 3.8.2. Recall

In this, we calculate true positive predictions from total positive predictions that might have been made. It shows a number of missing positive predictions. It is calculated as:

$$Recall = \frac{TP}{(TP + FN)} \times 100\tag{6}$$

#### 3.8.3. Accuracy

It is the most regular performance measure. It gives correct predictions to the total predictions.

$$Accuracy = \frac{(TN + TP)}{(FP + FN + TP + TN)}\tag{7}$$

3.8.4. F-Score

It shows steadiness between recall and precision.

$$F-score = \frac{2 \times (Precision + Recall)}{Precision + Recall} \tag{8}$$
