Scala for Machine Learning - Second Edition

Conditional random fields

Discriminative models such as linear, logistic regression, multilayer perceptron, and support vector machines are described in part 3 – Gradient-based Learning. However, it would make sense to introduce a discriminative alternative to HMM in this chapter dedicated to sequential data models.

The conditional random field (CRF) is a discriminative machine learning algorithm introduced by John Lafferty, Andrew McCallum, and Fernando Pereira [7:9]. The algorithm was originally developed to assign labels to a set of observation sequences as found.

Let's consider a concrete example to understand the conditional relation between the observations and the label data.

Introduction to CRF

Let's consider the problem of detecting a fault ...