Year: 2010
Type: conference-paper
Abstract: Data mining is the process of analyzing data and summarizing it into useful information that can be used in decision making or to increase revenue, cuts costs, or both.Decision tree is a widely used approach in data mining and machine learning for classification problems, which is considered to be self-explained models and easy to follow when compacted, namely if it has a reasonable number of leaves.Statistical Data mining methods such as Bayes' Theorem or Conditional Probability Theory (special case) is widely used method.Introducing the PIE Method that is a combination of Bayes' theorem and Entropy concept from information theory together to improve Bayes' Theory method by minimizing number of possible combination needed to solve a problem, without losing Information.A comparison of the results of the 3 methods will be done on an example that represents a small database.
DOI: 10.28945/1291
Authors: Ibrahem Tadros, Mohamad Al-Laham
Institution: Al-Balqa Applied University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W3140146572