Date of creation: 18. 8. 2017
It is possible to download software here.
Regularized logistic regression tool (regLOG) provides a fast and easy way of performing the L2-regularized logistic regression analysis using gradient descent optimization algorithm. L2 vector norm (controlled by the regularization parameter \lambda) can be used to optimize the regression coefficients in order to balance between bias and variance of the model.
The regLOG tool is programmed in the Python programming language (ver. 3.6). It can be used in combination with regularized linear regression tool. It provides a wide spectrum of outputs that can be used to assess the validity of the regression model: cost function evolution graph (functioning assessment), residual graph (validity assessment), coefficients graph (model visualization), etc. The tool also provides the data that can be used to test its functionalities.
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.