Neural Network Models for Combined Classification and Regression
Some prediction problems require predicting both numeric values and a class label for the same input.
A simple approach is to develop both regression and classification predictive models on the same data and use the models sequentially.
An alternative and often more effective approach is to develop a single neural network model that can predict both a numeric and class label value from the same input. This is called a multi-output model and can be relatively easy to develop and evaluate using modern deep learning libraries such as Keras and TensorFlow.
In this tutorial, you will discover how to develop a neural network for combined regression and classification predictions.
After completing this tutorial, you will know:
- Some prediction problems