Data Analysis Using Probabilistic Graphical Models

Abstract

Data mining is a multidisciplinary field, drawn from varying areas as artificial intelligence, database technology, data visualization and machine learning. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Data mining offers tools for discovery of relationship, patterns and knowledge from a massive database in order to guide decision about future activity. Probabilistic Graphical Models also known as Bayesian networks are popular and powerful tool in data mining. They have many applications in commercial decision support. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, credit risk analysis and banking sector. In this paper the knowledge discovery from various databases using Bayesian network and Bayesian classification techniques are discussed. Practical machine learning data mining open source software are used for knowledge discovery and data analysis.