A classification problem runs a neural network model to classify the inputs. For example, it classifies images of clothing into trousers, tops, and shirts. When we provide more inputs to the classification model, it will predict the value of the outcomes.
A simple example would be filtering an email as spam or not spam. Classification either predicts categorical class labels based on the training set or the values (class labels) when classifying attributes that are used in classifying new data. There are many classification models, such as Naive Bayes, random forests, decision tress, and logistic regression.
Here, we will work on a simple classification problem. To do this, use the following this code:
%matplotlib inline
