How to Develop a Neural Net for Predicting Disturbances in the Ionosphere
It can be challenging to develop a neural network predictive model for a new dataset.
One approach is to first inspect the dataset and develop ideas for what models might work, then explore the learning dynamics of simple models on the dataset, then finally develop and tune a model for the dataset with a robust test harness.
This process can be used to develop effective neural network models for classification and regression predictive modeling problems.
In this tutorial, you will discover how to develop a Multilayer Perceptron neural network model for the ionosphere binary classification dataset.
After completing this tutorial, you will know:
- How to load and summarize the ionosphere dataset and use the results to suggest data preparations