Skip to main content

M5 model tree for land cover classification

Buy Article:

$63.00 plus tax (Refund Policy)


Tree based regression models like a M5 algorithm represent a promising development in machine learning research. A recent study suggests that a M5 model tree algorithm can be used for classification problems after some modification. This letter explores the usefulness of a M5 model tree for classification problems using multispectral (Landsat-7 Enhanced Thematic Mapper Plus (ETM+)) for a test area in eastern England. Classification accuracy achieved by using a M5 model tree is compared with a univariate decision tree with and without using boosting. Results show that the M5 model tree achieves a significantly higher level of classification accuracy than a decision tree and works equally well to a boosted decision tree. Further, a model tree based classification algorithm works well with small as well as noisy datasets.

Document Type: Research Article


Affiliations: Department of Civil Engineering, National Institute of Technology, Kurukshetra, Haryana, 136119, India, 91‐1744‐238050

Publication date: 2006-02-20

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more