Let us see how we can use Keras to develop and evaluate neural network models for multi-class classification problems.
We will use the standard machine learning problem called the iris flowers dataset.
This dataset is well studied and is a good problem for practicing on neural networks because all of the 4 input variables are numeric and have the same scale in centimeters. Each instance describes the properties of an observed flower measurements and the output variable is specific iris species.
This is a multi-class classification problem, meaning that there are more than two classes to be predicted, in fact there are three flower species. This is an important type of problem on which to practice with neural networks because the three class values require specialized handling.