O'Reilly logo

Apache Mahout Essentials by Jayani Withanawasam

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Hidden Markov Model

A Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states.

HMM is a generative probabilistic model. HMM is used with data that is represented as a series of states from a series of observations. The transitions between hidden states are assumed to have the form of a (first-order) Markov chain.

HMM is mostly applied in temporal pattern recognition problems.

A real-world example – developing a POS tagger using HMM supervised learning

To demonstrate the HMM algorithm, let's take Part Of Speech (POS) tagging as an example.

POS tagging

POS tagging is important for many Natural Language Processing (NLP) tasks, such as word sense disambiguation, ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required