Logistic Regression Analytics Platform
The goal in Logistic Regression is to assign probabilities to model scores, creating a reliable
ranking system that can be used straightaway to evaluate the risk involved in financial and insurance
applications, to rank potential respondents in a marketing campaign, or to evaluate the risk of contracting a disease.
The Logistic Regression Framework of GeneXproTools builds on the models it generates with its evolutionary algorithms and
then applies the canonical logistic regression technique to estimate probabilities for each model score. And once you know
the probability of an event, you can also make categorical predictions and consequently infer crisp confusion matrices.
Thus, with its new Logistic Regression Framework, GeneXproTools offers a highly robust hybrid system in which sophisticated
multivariate nonlinear models are easily created by evolution and then empowered by traditional statistical modeling techniques.
With the Logistic Regression Framework of GeneXproTools you can: