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Baseline: Linear Regression
### Other Regressions (Matt)
Improve out of sample prediction accuracy by using regularization to avoid overfitting on the training set.
* Lasso regression
* Ridge r…
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I have been experimenting with `SGDRegressor` estimator to show if it is faster for large training set as compared to `Ridge` and **always finding that it is slower**.
This is quite opposite to [wh…
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consider using ridge regression for regularization at the test step:
`\argmin[\chi(l)^2 + \lambda(v(l).w)^2]`
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Hi,
I would like to ask, how to use minirocket for production or implementation phase. is there any way to save minirocket that was fitted in training data and use it for new dataset?
thank you
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A wishlist for probabilistic regression methods to implement or interface.
This is partly copied from the list I made when designing the R counterpart https://github.com/mlr-org/mlr3proba/issues/32 .…
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Description of the model(s) we will use. Start with linear regression, (we will most likely be using a variation of linear regression called **ridge regression**)
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The last cell calls joblin.dump(value=reg, filename=model_name)
But the model is called reg_model
eyast updated
3 years ago
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### Some of the most common ML Algorithms are listed below. Feel free to suggest other algorithms, not on the list. and we'll update it.
**Name**
- [ ] Multiple Linear Regression
- [ ] Lasso Re…
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### Evaluation
- [ ] [Confusion matrices](https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62)
- [Source 2](https://en.wikipedia.org/wiki/Confusion_matrix)
- [ ] [Precision…
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A very nice simple example.
https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-ridge-lasso-regression-python/
Please read before class