Java: Data Science Made Easy

Training a neural network

There are three basic training approaches:

• Supervised learning - With supervised learning the model is trained with data that matches input sets to output values
• Unsupervised learning - In unsupervised learning, the data does not contain results, but the model is expected to determine relationships on its own
• Reinforcement learning - Similar to supervised learning, but a reward is provided for good results

These datasets differ in the information they contain. Supervised and reinforcement learning contain correct output for a set of input. The unsupervised learning does not contain correct results.

A neural network learns (at least with supervised learning) by feeding an input into a network and comparing the results, ...