An Interactive Web Tool for Classification Problems Based on Machine Learning Algorithms Using Java Programming Language: Data Classification Software

Classification analysis is a frequently used approach in fields such as biomedical, bioinformatics, medical and engineering. In the field of health, it has become common to classify diseases based on risk factors by machine learning methods and to determine the effect sizes of these risk factors on the disease. There are many analysis tools used to guide researchers in classification analysis. While some of these tools are commercial and provide basic methods for classification analysis, some offer advanced analysis techniques and are desktop applications such as the WEKA environment. The WEKA environment includes comprehensive tools for classification analysis. However, use of the WEKA environment can be difficult and time-consuming, especially when a quick assessment is essential for users who do not have WEKA tool on their computer (doctors, etc.). Therefore; fast, comprehensive, free and easy to use analysis tool is required. The purpose of this study is to develop a user-friendly web tool (Data Classification Software; DCS) based on the classification algorithms of WEKA tool in Java programming language. The data classification software can be used on any device with an internet connection, which is independent of the any operating systems. In the developed web-based tool, data preprocessing module consists of missing value assignment, variable type conversion and normalization-standardization methods. Classification module encapsulates random forest, Naive Bayes, Bayes Network, j48, sequential minimal optimization, a rule and attribute selected classifier algorithms. This web tool can be accessed free of charge at http://biostatapps.inonu.edu.tr/DCS/.