Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

Dealing with categorical data is an essential part of data preprocessing in many machine learning tasks. Fortunately, encoding categorical data efficiently helps enhance the performance of machine ...

A variant of Banker and Morey's (1986) DEA model for controllable ordinal outputs. As opposed to the original model, this version allows the comparison of a Decision Making Unit (DMU) to other DMU's ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...