As we discussed in the first part of this series, how you handle data outliers can determine whether your big data project ends with a bang or flames out in failure. But before you even decide what to ...

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 ...

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 ...

This article explains how to programmatically identify and deal with outlier data (it's a follow-up to "Data Prep for Machine Learning: Missing Data"). Suppose you have a data file of loan ...