Classification algorithms help us to automatically learn how to make accurate predictions based on our observations. Starting from a set of predefined class labels, the classifier gives each piece of data a class label in accordance with the training model. Classification is somewhat similar to regression, which we studied in Chapter 2, Modeling Real Estate Using Regression Analysis. As well as regression, classification uses known labels of a training dataset to predict the response of the new test dataset. The main difference between regression and classification is that regression is used to predict continuous values, whereas classification works with categorical data.
For example, regression can be used to predict the future price of housing based on prices over the last 10 years. However, we should use the classification method...
