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Arvin Hsu commented on Stephanie Glen's blog post Comparing Model Evaluation Techniques Part 1: Statistical Tools & Tests

"I think your link to the L^1 RMSE is incorrect. Or at least there's no mention of the former in the latter article. The article did describe a way to evaluate model fit that was more outlier robust, but didn't call it was based…"

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Comparing Classifiers: Decision Trees, K-NN & Naive Bayes

A myriad of options exist for classification. In general, there isn't a single "best" option for every situation. That said, three popular classification methods— Decision Trees, k-NN & Naive Bayes—can be tweaked for practically every situation.OverviewNaive Bayes and K-NN, are both examples of supervised learning (where the data comes already labeled). …See More

Jun 19

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The Lifecycle of Data

The lifecycle of data travels through six phases:The lifecycle "wheel" isn't set in stone. While it's common to move through the phases in order, it's possible to move in either direction (i.e. forward, backward) at any stage in the cycle. Work can also happen in several phases at the same time, or you can skip over entire phases. In addition, if new information is…See More

Jun 18

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Jun 15

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Alternatives to R-squared (with pluses and minuses)

R-squared can help you answer the question "How does my model perform, compared to a naive model?". However, r2 is far from a perfect tool. Probably the main issue is that every data set contains a certain amount of unexplainable data. R-squared can't tell the difference between the explainable and the unexplainable , so it will go…See More

Jun 10

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