The QLattice is a software library which provides a framework for symbolic regression in Python.
[1] Since its creation, the QLattice has attracted significant attention, mainly for the inherent explainability of the models it produces.
[2][3][4] At the GECCO conference in Boston, MA in July 2022, the QLattice was announced as the winner of the synthetic track of the SRBench competition.
It is designed for easy interaction with the researcher, allowing the user to guide the search based on their preexisting knowledge.
[2][6] It has been used in research into many different areas, such as energy consumption in buildings,[3] water potability,[7] heart failure,[8] pre-eclampsia,[4] Alzheimer's disease,[9] hepatocellular carcinoma,[9] and breast cancer.