A computer program can be represented as a string of symbols using various possibilities. Each of these symbols is then represented by a binary number of six bits. In such manner the program is transformed into a string of 0 and 1. Each 0 is then interpreted as a step down and 1 as a step up in the walk. Inducing a decision tree is a form of automatic learning, where we extract knowledge from a set of examples and present it in a 2-dimensional form of a decision tree.
Classes are mutually exclusive, what means that the training object can belong to only one class.
Further, we distinguish between ordered and unordered discrete attributes. Continuous attributes are not suitable for learning a tree, so they must be mapped into discrete space. There are two types of nodes. Each internal node has at least two child nodes. External nodes , also called leaves or terminal nodes , are labelled with outcomes.