The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex (male or female), age, ...

"Quant strategies oftentimes get painted with a broad brush suggesting they are black boxes and no one really knows what's going on," said Scott Conlon, investment director for MDT Advisers, the ...

Previous algorithms for constructing regression tree models for longitudinal and multiresponse data have mostly followed the CART approach. Consequently, they inherit the same selection biases and ...

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of k-nearest neighbors regression to predict a single numeric value. Compared to other machine learning ...

Just as we might consult multiple experts about a problem and then combine their advice to come to a consensus decision, repeated statistical analyses on the same data can be combined to form a single ...