Data Classification mainly refers to a way of organizing/categorizing the data by assigning a label/class to a set of data. For example, from the age, we can the class Infants, children, adolescents, adult, or older adult to a person. It is very easy to classify if the data is very small or the feature set (here it is only the age of the person) is very small. What will happen, if the amount of data is very large? We can use different ML algorithms to perform the classification task on a large dataset with hundreds of the features. In this post, we will learn how to classify a set of data using the popular supervised Naive Bayes algorithm using Python language. Continue reading…