Related Issues (20)
- File saving/loading neural layer parameters
- Adding multiple crossover operators
- Making the self-adaptive methods selectable at runtime
- Module not found error on Windows & Mac HOT 4
- Make option setting and getting symmetrical (Python bindings) HOT 3
- Segmentation fault if `y` has shape `(N,)` for some `N` HOT 4
- Non-standard use of hyphens in variable names
- `max_index` leads to unexpected bias in prediction array HOT 2
- Performing `xcs.predict(X)` alters the model when it should not (supervised learning) HOT 4
- Initialization of center-spread rectangular conditions may be suboptimal HOT 3
- Support early stopping or maybe even callbacks HOT 2
- Add support for pickling XCSF
- Deserialization of tree-GP and DGP conditions segfaults HOT 1
- make Python library (mostly) sklearn compatible HOT 8
- accept 1-D inputs to fit / predict / score as well as 2-D
- add warm_start parameter to Python fit() and default False HOT 2
- add random number seed parameter
- `XCS().get_params()` does not contain the action config HOT 9
- `random_state` parameter does not conform to sklearn interface HOT 2
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