Comments (1)
See #88. There are now two new things:
PolynomialChaosExpansion.weights
, which returns sample weights used in training. This might not give what you expect (e.g., the weights are positive, but won't sum to 1)PolynomialChaosExpansion.integration_weights()
, which returns weights more akin to weights for a biased ensemble. The weights will sum to 1, but some weights might be negative.
I am not sure which of the above you want/need. We can talk about it if the above isn't clear.
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Related Issues (20)
- Distribution Bounds not working correctly
- Fast idistinv for Jacobi Polys bug
- Fix pytest run in action build context HOT 16
- Complete readme file HOT 1
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- Distributions docs
- Polynomial spaces docs
- Demos docs HOT 2
- investigate rtd warnings
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- Index set docs
- setup file does not set the correct environment libraries HOT 2
- Update documentation for setup.py HOT 1
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