Fuzzy logic trees are a machine learning method that applies the principles of fuzzy logic
to standard logical decision trees. They are trained by simulated annealing.
This website will be updated with results and succesful applications.
The fuzzy operation used is the biased ordered weighted average. Each node is binary, and moves
continuously from AND-like to OR-like operation. The less important input is interpolated
towards the dominant one. A C program to generate the trees is available, with an auxiliary
Java program for viewing the trees graphically.
Simulated annealing main loop
Loads a csv file |
Coverts csv to internal data format
Internal data format
Logic for tree |
Fuzzy logic operations |
main program file |
All software provided free. Please cite my Master's thesis Fuzzy Logic Trees, University of Leeds, Faculty of Biological Sciences (2005), by Malcolm A. McLean