Multiple Regression As A Machine Learning Algorithm

Multiple Regression As A Machine Learning Algorithm

Multiple regression as a machine learning algorithm with full implementation in Python using Sci-kit Learn module

Previously I wrote a couple of pieces on multivariate modeling but they both focused on time series forecasting. If curious, go ahead and check out the posts on vector autoregression and panel data modeling. Writing on multivariate regression (i.e. multiple linear regression) was always on my list but something else was on its way — I started a series on anomaly detection techniques! Once started that series, I could not stop until I wrote 11 consecutive posts. Today I’m back with multiple regression and here’s the plan — first I’ll define in broad terms what a multiple regression is, and then list some real-world use cases as examples. The second part is going to be a rapid implementation of multiple regression in Python, just to give a broad intuition. In the third part, I’ll dive a bit deeper following the typical machine learning workflow. I’ll end with some additional points to keep in mind while implementing linear regression

machine-learning python regression scikit-learn data-science

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