MACHINE LEARNING

Detailed explanation-1: -The confusion matrix is used when there are two or more classes as the output of the classifier. Confusion matrices are used to visualize important predictive analytics like recall, specificity, accuracy, and precision.

Detailed explanation-2: -A confusion matrix is a table that is used to define the performance of a classification algorithm. A confusion matrix visualizes and summarizes the performance of a classification algorithm.

Detailed explanation-3: -A Confusion matrix is an N x N matrix used for evaluating the performance of a classification model, where N is the total number of target classes.

Detailed explanation-4: -A confusion matrix is a tabular way of visualizing the performance of your prediction model. Each entry in a confusion matrix denotes the number of predictions made by the model where it classified the classes correctly or incorrectly.