Comments (3)
inf: output max system size for stack type
nan: output 0
- make safe function in base Node class
- call safe on return values of evaluate function for division, exponent, and log nodes
from feat.
reopening this issue because there are still issues with inf and nan features, especially when normalizing features. need to come up with a better strategy to address this.
from feat.
it seems like nans were coming from eigen's normalize function. this block manually checks for near-zero columns in X before normalizing.
from feat.
Related Issues (20)
- Segmentation fault HOT 8
- Eigen is not at bitbucket anymore HOT 2
- macOS installation
- make conda package
- add FeatRegressor, FeatClassifier derived classes
- handle depth more accurately
- Custom function HOT 1
- segmentation fault in parallel mode HOT 7
- Logistic regression seems falling HOT 2
- Cartesian Genetic Prog HOT 3
- Memory leak in multiclass HOT 12
- What's the best development method for this package? HOT 2
- The document of install and example is loss. HOT 1
- Operator selection syntax/ issue HOT 8
- Feat.Predict(x) causing Segmentation fault HOT 1
- Propagate feature weights and offsets to leaves of equations when normalize=True
- Double decimal points in coefficient HOT 2
- ModuleNotFoundError: No module named 'feat.pyfeat' HOT 1
- Symbolic model does not evaluate to the same values as `predict` HOT 2
- Could not find id = 5257 in archive. HOT 1
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from feat.