"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 ...

Decision tree regression is a machine learning technique . To predict the output y for an input vector X, the tree structure encodes a set of if-then rules such as, "If the value of X at index [2] is ...

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 ...

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 ...

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, ...