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I have a large matrix (150000 by 32000) I am trying to run a linear SVC using scikit-learn to perform a lasso regression
``` lsvc = LinearSVC(C=0.01, penalty="l1", dual=False).fit(df, y) ```
I …
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Hi,
**Describe the bug**
I took a look at the tutorial on how to find sparse solutions[https://github.com/cvxpy/cvxpy/blob/master/examples/notebooks/WWW/sparse_solution.ipynb] and have a question …
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3D printed stylus is pretty good still sometimes might be worth to put at the end a metal tip, sharper and that does not break. Because the one used has been pivoted so many times that the tip is not …
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### Describe the bug
The computation of the duality gap in `_dual_gap(emp_cov, precision_, alpha)` of `GraphicalLasso` uses the definition from `Duchi et al., 2012`.
However, their duality gap is…
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[LassoLars](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLars.html?highlight=lassolars#sklearn.linear_model.LassoLars) can be quite imprecise at low regularization value…
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It seems to me that the Lasso model-fitting API is not designed for the user to simply pick a particular choice of lambda and fit a model with that particular choice. Having looked at the source code …
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Jas's paper on this seems like a nice way to include arbitrarily many covariates without needing to worry about degrees of freedom? Plus then you don't need to worry as much about selecting the few y…
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The graphical lasso is quite unstable on very ill-conditioned matrix. It is a well known issue that arises from the fact that it is a very optimization problem.
Adding a small amount of l2-regulari…
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Currently we have three R wrappers. They differ in functionalities, the abstraction level of arguments they take in, and where they are used in testsuites. Eventually their functionalities will be s…
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Just tried using IMageMonkey from a new iPad (entry level 6th gen 2018) with an Apple-pencil,
conclusion - very positive - it's a bit better than a PC/laptop + wacom, it's the best experience I've …