In a previous post, I explored how one might apply decision trees to solve a complex problem. This post will explore the code necessary to implement that decision tree. If you would like a full copy of the source code, it is available here in zip format. Entropy.java – In Entropy.java, we are concerned with [...]
Posts Tagged ‘decision trees’
Decision Tree Learning Acting As A Cardiologist
Abstract—Decision trees are one of the most widely used methods of inductive inference. They can be used to learn discrete or continuous valued hypotheses and create compact rules for evaluation of a set of data. An advantage of decision and regression trees is that they are robust to noisy data, which makes them perfectly suited [...]