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In machine learning, collinearity is a complex puzzle for both seasoned professionals and newbies alike. Machine learning (ML) algorithms are optimised for predictive accuracy not explainability of predictors on the target. Also, most solutions for addressing collinearity, such as the ‘Variance Inflation Score’, and ‘Pearson’s cross-correlation analysis’ potentially leads to massive information loss in pre-processing.
DATA SCIENCE. ANALYTICS. PYTHON Photo by Matt Walsh on Unsplash As we mentioned in the first article in a series dedicated to the study of missing data, the knowledge of the mechanism or structure of “missingness” is crucial because our handling method would primarily depend on it. In Handling “Missing Data” Like a Pro — Part 1 — Deletion Methods, we have discussed deletion methods. In Handling “Missing Data” Like a Pro — Part 2: Imputation Methods, we discussed simple imputation methods.
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