Kernel regression tool


Ing. Zoltán Galáž, Ing. Jiří Mekyska, prof. Ing. Zdeněk Smékal, CSc.

Date of creation: 28. 5. 2017


It is possible to download software here.


Kernel regression tool (regK tool) provides a fast and easy way of performing the non-parametric (kernel) regression analysis. This type of regression is especially sufficient in cases when we have lots of training data samples. In these cases, the kernel regression can outperform (robustness, performance) classical parametric approaches, which would require great complexity (lots of parameters) to provide comparable results.

The regK tool is programmed in the Python programming language (ver. 3.5.2). It provides a wide spectrum of kernel function: linear kernel, radial basis kernel, gaussian kernel, polynomial kernel, etc. It also provides several vector distances metrices such as: Euclidean distance, manhattan distance, hamming distance, etc. The tool also provides the data that can be used to test its functionalities. The data are based on the real-world example of retail-sales price estimation.


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.


To negotiate the license terms of use of this software please contact the responsible person Ing. Lukas Novak at Technology Transfer Office, Brno University of Technology, Kounicova 966/67a, Veveří, 60200, Brno, Czech Republic,