chapter  4
Decision Trees: Theory and Algorithms
ByVictor E. Lee, Lin Liu, Ruoming Jin
Pages 34

One of the most intuitive tools for data classification is the decision tree. It hierarchically partitions the input space until it reaches a subspace associated with a class label. Decision trees are appreciated for being easy to interpret and easy to use. They are enthusiastically used in a range of business, scientific, and health care applications [12,15,71] because they provide an intuitive means of solving complex decision-making tasks. For example, in business, decision trees are used for everything from codifying how employees should deal with customer needs to making high-value investments. In medicine, decision trees are used for diagnosing illnesses and making treatment decisions for individuals or for communities.