Troubleshooting

This page collects common installation and runtime issues.

Import Errors

If importing Ex-Fuzzy fails after installing from source, verify that the package was installed from the repository root:

pip install -e .

For documentation builds and examples, install the docs extra:

pip install -e ".[docs]"

EvoX or JAX Installation

The EvoX backend is optional. Install it only when you need GPU-accelerated optimization:

pip install "ex-fuzzy[evox]"

If JAX cannot find a compatible accelerator, first confirm the CPU backend works:

from ex_fuzzy import BaseFuzzyRulesClassifier

clf = BaseFuzzyRulesClassifier(backend="pymoo")

Then check the JAX installation that matches your platform and CUDA version.

Slow Training

Training time grows with the number of rules, antecedents, generations, and population size. Start with a small run and scale gradually:

clf.fit(X_train, y_train, n_gen=10, pop_size=20)

For larger datasets, compare backend="pymoo" and backend="evox" with the same split and seed before committing to a backend.

Unexpected Accuracy Differences

Fuzzy rule optimization is stochastic. Differences can come from the train/test split, optimizer seed, backend, fuzzy partitions, or population settings. For published results, run multiple seeds and report the mean and standard deviation.

Documentation Build Issues

From the repository root, install the documentation dependencies and rebuild:

pip install -e ".[docs]"
cd docs
make clean html

The generated HTML is written to docs/build/html.