Computational Modelling Group

• Login/Register

You are here:

• CMG Home
• Research
• Classification

Classification

Classification is the method of assigning items to groups (known as classes) based on information about the items. This can be done manually, but is often done automatically by algorithms such as K-Means or Maximum Likelihood, based upon quantitative information about the items.

Classification techniques can be split into two types:

Unsupervised classification can be performed with no a-priori knowledge of the data. For example, a satellite image could be classified into different land-cover classes based entirely on the spectral information inherent in the image, without any human input about what the classes should be.

Supervised classification requires some input about the classes into which the data should be split. For example, the supervised classification equivalent of the example above would be to give the classification routine a list of classes, with examples of the spectra of pixels that fit into those classes. The classification algorithm would then use this training data when classifying the rest of the data.

Classification is a technique that is used in many areas of research. Some fields, such as Remote Sensing/Earth Observation, use classification as a fundamental processing technique, whereas in many other fields data is classified to enable easy visualisation and statistical analysis.

For queries about this topic, contact Robin Wilson.

View the calendar of events relating to this topic.

Projects

People