In a machine learning domain performance is one of the measure things that we want to know how our model is performing. There are many techniques to measure the performance of the model. Today we will discuss Accuracy.

Accuracy is defined asthe correctly classified points by a total no of points on the test set.

Accuracy = #correctly classified points / Total no of points in testset

Suppose we have 1000 data points in which 600 are positive and 400 are negative. Our model predicted 580 points positives and 20 negatives for positive data points and for negative it’s predicted 350 points positive and 50 negatives.