This repository provides framework for conjectural deductive programming (CDP), a new strategy for solving classification problems. CDP works by attempting to evolve a set of rules of inference that form a deductive system that can properly classify a given set of data values. Rules of inference are represented as program trees (i.e. Lisp programs), and they can be generated and mutated by the same means that are traditionally used in genetic programming.
The file main.clj contains code that uses CDP to attempt to classify the popular Iris Flower dataset. At the moment, attempts at classifying this dataset are largely unsuccessful, unless you only run it with a trivially small number (2-4) of data values. I'm actively working to make the framework more effective at solving this problem, and hopefully others.
To run the code, REPL into the cdp.main namespace and run the iris-evolve function. iris-evolve takes 4 arguments, steps, data-points, statement-cap, and rule-cap. The meaning of each of these arguments is explained in the docstring for the function. Sane values for these arguments are 50, 3, 8, and 200, respectively.
MIT License
Copyright (c) 2020 Ella Hoeppner
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