The MGB Framework is a collection of tools designed to facilitate the processing, visualization, understanding and mining of all types of symbolic and numerical time series and sequence datasets. The MGB Framework has been developed by Mathieu Guillame-Bert since 2010. The MGB framework is composed of three parts:
Honey is a compact and high level flow-oriented programming language designed to facilitate the pre/post processing and analysis of symbolic and numerical time series and sequences datasets. Honey can seemingly be applied on static dataset and real time data streams (learn more)..
Event Viewer is a powerful visualizing tool for time series, time sequences and other symbol or scalar temporal datasets. Event Viewer has unique features which allow for a powerful understanding of data. Event Viewer can be used to study static data and real time data flows. Event Viewer can interact seemingly with Honey (learn more)..
Titarl is a temporal data mining algorithm able to extract temporal rules from symbolic time series and time sequences (SSTS). The rules can be interpreted, used for predictions, or used for further analysis (learn more)..