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In terms of functionality, the mid-term end goal is to achieve an offering of ML algorithms and pre-processing routines comparable to what is currently available in Python's [`scikit-learn`](https://s…
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I am using rocket transform and ridge regression to predict timeseries data.
```
x_train shape : (800, 644, 36)
x_test shape : (200, 644, 36)
y_train shape : (800, 644 * 1008)
y_test shape : …
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may you clarify
why intercept is not calculated separately in
https://github.com/wiqaaas/youtube/blob/master/Machine_Learning_from_Scratch/Lasso_Regression/Lasso_Regression_using_Coordinate_Descen…
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During `RidgeRegression.fit()`, we group on `['sample_block', 'label']` but not on `'alpha'`. This becomes a limiting factor on our scalability due to PyArrow limits, which constrain the number of 8-b…
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At the moment the features are standardized before the evaluation loops (mean removal and dividing by variance) with the following:
`data_features = (data_features - data_features.mean()) / data_fea…
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@gbifvyihk
Can you verify the following for me?
It would seem that the scoring method/function for regression models (e.g. Ridge Regression) is the `score(X,y)` method/function. This function. w…
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**Version 0.2**
Id | Models | Code | Test | Documentation
--- | ---------------------------------- | -------- |--------|--------------…
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Dear Steffen,
I believe there are some errors in the expression employed to compute the standard errors of the ridge linear coefficients (ridge:::vcov.ridgeLinear). Specifically, it always penalize…
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Use L1, L2 and elasticNet Regression to counter overfitting.
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try ridge regression because G/xG/g/a1/a2 are too highly correlated.