Fuzzy regression tree

Generates fuzzy inference system (FIS) using regression tree algorithm and ANFIS training

The archive includes genfis4.m that generates Mamdani- and Sugeno-type FIS using regression tree algorithm to extract fuzzy rule information from data set. It is based mostly on Fuzzy Logic Toolbox but it has required to modify Toolbox's fuzzy rule building principle. As a result some original m-files was adapted for this new fuzzy rule structure. They are marked with the last 'x' symbol and included in the archive (e.g., getfisx.m, evalfisx.m etc.) Though some Toolbox's m-files still work (e.g., addvar.m, plotmf.m etc.)

Remarks:
- before you start you should create MEX files by commands:
mex src/evalfisxmex.c
mex src/anfisxmex.c
- if you want to use your own regression tree algorithm you need to rewrite treefun.m (see example2.m for MATLAB's fitrtree usage);
- see example1.m and example2.m for fuzzy regression tree usage.
Known problems:
- it supports only regression tree without missing values for predictors and the response;

- it doesn't work if the resulting tree consists only one node (leaf);

- if some predictors are encountered in none of the branch nodes you can't use ANFIS training (evalfisx.m still works).