QLattice
Symbolic regression machine learning algorithm
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- 2 chapters
Related on Lably
Through Library (computing), Python (programming language) and Microsoft Windows
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.
Features
The QLattice works with data in categorical and numeric format. It allows the user to quickly generate, plot and inspect mathematical formulae that can potentially explain the generating process of the data. It is designed for easy interaction with the researcher, allowing the user to guide the search based on their preexisting knowledge.
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Scientific results
The QLattice mainly targets scientists, and integrates well with the scientific workflow. It has been used in research into many different areas, such as energy consumption in buildings, water potability, heart failure, pre-eclampsia, Alzheimer's disease, hepatocellular carcinoma, and breast cancer.