Comments (2)
cod3licious
commented on May 24, 2024
Hey @fkhan00 : the main bottleneck is the feature generation using the sympy library (which computes the different feature formulas to make sure there are no redundant features being generated etc.). Since it's probably not possible to improve a lot there with cython, I'm not sure if you'll really get a huge performance boost. But if you try it and it helps, I'd be happy about a pull request! :) good luck!
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Sandy4321
commented on May 24, 2024
better without cython pls, since it is usually problem to install code based on cython
thanks
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Related Issues (20)
- ImportError: cannot import name 'AutoFeatRegressor' from 'autofeat' HOT 5
- Original feature names are changed to x000, x001, x002,etc., How to avoid this? HOT 1
- Cannot reproduce results HOT 1
- Parallelization
- Issues with sympy module HOT 5
- AttributeError: module 'sympy.core.core' has no attribute 'add' HOT 4
- Data validation error when using Buckingham's Pi Theorem on Classification task HOT 1
- Is it possible to use autofeat without exceeding memory of the system? HOT 3
- possible point for verification HOT 3
- How to transform new data? HOT 1
- Speed up tranform() HOT 6
- MemoryError: Unable to allocate 2.05 GiB for an array with shape (501, 550174) and data type float64
- pandas corr is too slow; use numpy instead HOT 1
- Correlation matrix can have inconsistent column and row names HOT 1
- Allow user to pass dict of Pint objects/ureg
- Input contains NaN, infinity or a value too large for dtype('float32') on fit_transform HOT 2
- ufunc '_lambdifygenerated' did not contain a loop with signature matching types (<class 'numpy.dtype[float32]'>, <class 'numpy.dtype[float32]'>) -> None HOT 6
- How to choose sin(x) and cos(x) etl. as features? HOT 1
- Scaling and Autofeat HOT 2
- [enhancement] add predict_proba for classifiers HOT 11
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