Tag: Predictive Models

Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

In this article, we'll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human...

Justified Algorithmic Forgiveness?

Last week, Paco Nathan referenced Julia Angwin’s recent Strata keynote that covered algorithmic bias. This Domino Data Science Field Note dives a bit deeper into some...

Item Response Theory in R for Survey Analysis

In this guest blog post, Derrick Higgins, of American Family Insurance, covers item response theory (IRT) and how data scientists can apply it within a project. As...

Data Science is more than Machine Learning 

This Domino Data Science Field Note provides highlights and video clips from Addhyan Pandey’s Domino Data Pop-Up talk, “Leveraging Data Science in the Automotive Industry”. Addhyan...

Benchmarking Predictive Models

It's been said that debugging is harder than programming. If we, as data scientists, are developing models ("programming") at the limits of our understanding, then we're...