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A Python package to build predictive linear and logistic regression models focused on performance and interpretation

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# Integration of git-changelog package and invoke command for easier development [Pietro integrates some best practices within Cobra #154](https://github.com/PythonPredictions/cobra/issues/154) ## Additions made Added some automated development tasks through the [invoke](https://www.pyinvoke.org/)...

enhancement

# Task Title Task: Update requirements specifications ## Task Description Right now, our requirements.txt only lists the required packages, not a python version. It takes some "figuring out" (searching on...

good first issue

# Task Title Task: Pietro integrates some best practices within Cobra ## Task Description Pietro proposed the following: - commit message style - good practices (change log, etc) - invoke:...

enhancement
good first issue
data engineering

# Task Title Task: Improve contributing documentation & add recording ## Task Description This task bundles material to be merged within the [contribution guidelines](https://github.com/PythonPredictions/cobra/wiki/Contributing-guidelines-&-workflows). Let's use the first milestone of...

good first issue

Refactor code according to PEP8. This makes PR #132 obsolete. We only use black instead of the other proposed linters and typechecks in that PR.

This method currently plots and compares the predictions versus the actuals. No post-processing of the data is done, which makes the plot not visually attractive, aspecially for big test sets....

enhancement
good first issue

# Story Title [Improved industrialization support: persisting of model (configuration), reapeated model scoring, model monitoring](https://github.com/PythonPredictions/cobra/issues/127) ## Changes made See files committed. This is a draft pull request only for now,...

enhancement

# Clearer documentation about how to industrialize Cobra models We've received a couple of questions in the past months about how Cobra models can be industrialized. Let's interpret that as...

====> **Do not merge yet! See below for explanation.**

enhancement

# Allow more tuning of the model hyperparameters. While working on #126, I noticed that in the constructor of LogisticRegressionModel, a few hyperparameters are chosen as follows: ``` def __init__(self):...

enhancement