Date of creation: 7. 4. 2017
It is possible to download software here.
Publication to be cited
MEKYSKA, J.; FAÚNDEZ ZANUY, M.; MŽOUREK, Z.; GALÁŽ, Z.; SMÉKAL, Z.; ROSENBLUM, S. Identification and Rating of Developmental Dysgraphia by Handwriting Analysis. IEEE Transactions on Human-Machine Systems, 2016, roč. PP, č. 99, s. 1-14. ISSN: 2168-2291.
GALÁŽ, Z.; MEKYSKA, J.; MŽOUREK, Z.; KISKA, T.; SMÉKAL, Z.; REKTOROVÁ, I. Degree of Parkinson’ s Disease Severity Estimation Based on Speech Signal Processing. In Proceedings of the 39th International Conference on Telecommunication and Signal Processing, TSP 2016. 1. 2016. s. 503-507. ISBN: 978-1-5090-1287-9.
In the field of biomedical signal processing (e.g. pathological speech signal processing), often it is necessary to use binary regression analysis. For this purpose, the researchers nowadays use multiple sophisticated regression techniques and metrics to evaluate regression models. Regression grid search tool (RLCT) provides an easy and fast way to plot so-called learning curves to visualize if we deal with the high-bias or high-variance problem and consequently adjust the following analysis setup.
Software RLCT provides 5 possible regression techniques: Classification and Regression Trees (CART), Ordinal Regression (OR), Linear Regression (LR), Support Vector Machines Regression (SVMR), Gaussian Process Regression (GPR). It also provides 10 metrics evaluating the quality of regression process: Gini Index (GI), Absolute Error (AE), Mean Absolute Error (MAE), Squared Error (SE), Mean Squared Error (MSE), etc. The RLCT software is written in the MATLAB programming environment. The testing scripts can be used to test the functionality of the software.
This work was supported by projects AZV 16-30805A and LO1401. The described research was performed in laboratories supported by the SIX project; the registration number CZ.1.05/2.1.00/03.0072, the operational program Research and Development for Innovation.