Decision Tree Algorithm: A Survey

Decision tree is one of the popular techniques in the research community to be used to develop decision making approaches. Over the period of almost four decades, a wide variety of applications of decision trees for providing good quality solutions in the different areas of life including technological pitfall, health hazards , social and geographical hitches, etc have been tried by several authors. The kind of work to be stated includes Object recognition using binary DT, Face detection, Diagnosing failures in large Internet sites, Prognostic decision making in breast cancers, Speech emotion recognition, Flood probability mapping, Automated Detection of Deceptive Language, Knowledge Discovery on Climate and Air Pollution and Fault Detection. Some pieces of works have even put commendable effort for development of DT and considerable evolution in the technique is observed. Some noteworthy works are effective decision tree design technique with the help of priori statistics, overcoming the shortcoming of ID3’s using a new DT algorithm that united the ID3 and Association Function (AF) as well as an algorithm that combines principle of Taylor Formula with information entropy solution of ID3, alternating decision tree (ADTree) technique, etc. Here we are making a sincere effort to present some important applications of DT discussed by different authors through their valuable work as well as the variety of evolutionary aspects of DT put forward by them for the entire research community.