A Python package helps get an Optimal Linear Regression Model by removing insignificant variables and solve multicollinearity problems

Dr. Shouke Wei from Deepsim Intelligence Technology Inc. (Deepsim) developed a small package called modelselect, which can help you easily create an optimal linear regression model by removing the insignificant and the multicollinearity predictor variables. This package can reduce the interactive process and tedious work to run the model, estimate it, evaluate it, re-estimate and re-evaluate it, etc. You can find this package on the web of PyPI and GitHub page.

If you are interested in how to use this package, please read this post.












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