Monthly Archives: November 2016

Visualizing the Effects of Multicollinearity on LS Regression

Greetings, my blog readers! In this post I would like to share with you two interesting visual insights into the effects of multicollinearity among the predictor variables on the coefficients of least squares regression (LSR). This post is very non-technical … Continue reading

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Test-Driven Data Analysis (and its possible application to the LS Regression)

I have recently attended a PyData meetup in London where Nicolas Radcliffe gave a nice talk on the concept of Test-Driven Data Analysis (TDDA). Here is a link to the slides that he presented. Essentially, the idea behind TDDA is born from … Continue reading

Posted in Machine Learning | Tagged