Put some ART in WEKA

WEKA is a fantastic data mining tool but lacked functionality to use it in ERP reserach. This is going to change soon thanks to Jindrich Ciniburk and Václav Souhrada . Introduction: The process of preprocessing, processing and classification of EEG/ERP signals is a very complex task, for which various software tools are used. However, some methods are used frequently in different stages of the task solution. Thus we decided to use advantages of software WEKA, which represents very powerful framework with strict rules. It also contains a great amount of methods such as wavelet transformation, Bayes classificators in many versions, artificial neural networks, decision trees etc. However WEKA software does not include some algorithms and data structures important for EEG/ERP research and signal processing. At first we designed a new way how WEKA could handle relational data, because complex data obtained by EEG devices need to be organized in 1:N relationship at least (see Figure 1). This proposal includes design of a new data file format and also new methods for data preprocessing and preparation to enable their usage within standard methods included in WEKA. This part is based on SQL queries; it means that it is not necessary to store data only into files. WEKA and our plug-in can read data directly from database. Read here