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When using settings = CreateDefaultTemporalCovariateSettings(), running the getPlpData + createStudyPopulation works fine, but when running the lasso logistic regression model I receive the error belo…
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The first part is there, but there isn't much in the analysis section. neither methods describing the analysis, nor results. a few tables are referenced but they don't show up.
It seems the project…
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LASSO regression is a useful technique for building sparse models and aiding in variable selection. Suggest we implement it as an alternative to the existing methods.
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Right now the basic linear models is not supported. Which is a shame, cause they are often quite useful.
From [sklearn.linear_model](https://scikit-learn.org/stable/modules/classes.html#module-skle…
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Always funny how these projects start, one goes from like 100 users that understand the tremendous opportunity of fast in-memory computing --- and then 2-3 years later 10 million people heavily rely o…
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Does a prediction model with variable selection procedure (e.g. lasso regression) consider group shinkage (e.g. group lasso)? For example, if a categorical variable with C levels is converted to C-1 b…
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### ML-Crate Repository (Proposing new issue)
:red_circle: **Profinity filter** :
:red_circle: ** Aim is to classify whether the used text is abusive or not ** :
:red_circle: **Dataset** :
:red_ci…
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It would be very good to add a parameter on the plot_time_series_regression function to control the type of model you would like to test. Since this function is for feature selection, it would be grea…
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See [here](https://iangow.github.io/far_book/prediction.html#features) for starter code.
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@tlienart
1. **All Subset (Best K Subset)**:
I've got parsimonious code for All Subset Regression which might have a nice home in this package that I'd like to share.
While it's much faster than …