Data Preparation: Know Your Records!
Data preparation in data mining and predictive analytics (dare I also say Data Science?) rightfully focuses on how the fields in one’s data should be represented so that modeling algorithms either will work properly or at least won’t be misled by the data. These data preprocessing steps may involve filling missing values, reigning in the effects of outliers, transforming fields so they better comply with algorithm assumptions, binning, and much more.(more…)
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