ID3 decision tree algorithm
Abstract—This paper describes how the ID3 algorithm is used to classify a set of data. ID3 consists in building a simple tree with branches that lead to a particular decision (leafs).
The process to classify a set of data consists of two main processes. First, the training mechanism builds a decision tree with a given set of training data. This information contains all values of each attribute, that will lead to a final decision, also called target attribute. Therefore all leaves in the tree will contain one of the values of the target attribute. The classifying data set will contain all of the attributes that will be used to determine the value of the target attribute of that data.
Mykola Shevchenko, 2016