Published Paper Details:

More and more data is generated in Internet due to people usage of internet applications for online shopping, insurance has increased leaps and bounds. Which generates huge amounts of which when mined in efficient way will give enormous benefits not only to individuals but also to society. So to tap the potential day by day various methods related to data science and machine learning have been developed. The decision tree classification method is one of the applications of data mining techniques. The decision tree method is a popular and effective technique for classification problems, as it has advantages such as simple algorithm, clear logic, and easy adaptability to different data types. In this paper by overcoming the defects of ID3 decision Tree algorithm development of this application, a new feature probability based decision tree algorithm has been used in the construction of a decision tree model based on the data given, The feature based applications are noted prior to implementation of FPBDT algorithm for generating decision. This can help project managers and decision makers to extract valuable insights from the data and make informed decisions.