Outliers deviate from the norm—significantly enough to give marketers pause. But outliers can tell us more about our data, how we gather it, and what is in it, if we examine the entire data set ...

Machine learning algorithms aren't just technological novelties relegated to tasks like picking out faces in crowded places. In the enterprise, they can surface patterns and relationships that would ...

Outliers have the potential to skew analysis when they aren’t properly accounted for. Addressing outliers, specifically in trade cost analysis (TCA) data, is crucial for traders because it ensures the ...

After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft Research now uses a full code sample and step-by-step directions ...

Robust estimation and outlier detection play a critical role in modern data analysis, particularly when dealing with high-dimensional datasets. In such contexts, classical statistical methods often ...

Data analytics deals with making observations with various data sets, and trying to make sense of the data. When dealing with very large data sets, automated tools must be used to find patterns and ...

At the impeccably timed “Who Will Win the Spam Wars” roundtable at the BigThink conference this morning, Google’s Matt Cutts, Bing’s Harry Shum and Blekko’s Rich Skrenta got together to discuss recent ...