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https://mp.weixin.qq.com/s/avETGVE8_5I5CrvljG2Tqg
ixxmu updated
2 years ago
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Hi all!
When I made the educational project “Predicting House Sale Prices” based on ames dataset I decided to experiment with different types of linear regression – simple OLS and Ridge regression an…
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I was surprised to see that the regularization term is divided by n_samples. This is not standard.
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/neural_network/multilayer_perceptro…
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Hi,
I built v2.2 (15b858d3fb) and ran our internal tests. It is now failing to converge in step 1 using our binary phenotypes. It is the same data and parameters so I'm a little confused what is di…
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I suspect that using sklearn here is very memory inefficient. To compute a Ridge you need to assemble X.T @ X and X.T @ y and then solve a linear system. Time series packages assemble X.T @ X and X.T…
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#### Describe the workflow you want to enable
I'd like to have
```python
reg = Ridge(positive=True)
reg.fit(X, y)
print(reg.coef_)
```
and only get non-negative print results.
Adding `positi…
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I would like to use my data set with anomaly detection library but I got this error all the time which is in enclosed file.
…
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**Describe the bug**
ridgeParameters has no effect in distributed Ridge Regression
See also: https://github.com/intel/scikit-learn-intelex/discussions/620
I also reproduced this with C++ interf…
xwu99 updated
3 years ago
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Fixed by adding an `__init__.py` to `aec` submodule and adding `connectivipy.aec` to packages list in setup.py.