Akansha Yadav walks through calculating accuracy from a confusion matrix. Accuracy equals (TP + TN) divided by all four components. It shows the percentage of correct predictions across both positive and negative classes.
So let's see how accuracy is calculated on the basis of the confusion matrix. So confusion matrix gives us 4 values: TP, FN, TN, FP. So true positive, false negative, false positive, and true negative. So accuracy is basically the overall performance of the model. It will tell you the parameter that by how many percent the performance of the model is. So to calculate the accuracy, you have to do the addition of true positive value and true negative value divided by true positive plus true negative plus false positive plus false negative.
