Binary Classification

Binary Classification algorithms is a prediction the score indicates the system’s certainty that the given observation belongs to the positive class. To make the decision about whether the observation should be classified as positive or negative, as a consumer of this score, you will interpret the score by picking a classification threshold and compare the score against it. Binary classification accuracy metrics quantify the two types of correct predictions and two types of errors. It is the task of classifying the elements of a given set into two groups on the basis of a classification rule.