Paper: A Default First Order Family Weight Determination Procedure For WPDV Models

ACL ID W00-0724
Title A Default First Order Family Weight Determination Procedure For WPDV Models
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000
Authors

Weighted Probability Distribution Voting (WPDV) is a newly designed machine learning algorithm, for which research is currently aimed at the determination of good weighting schemes. This paper describes a simple yet effective weight determination procedure, which leads to models that can produce competitive results for a number of NLP classification tasks. 1 The WPDV algorithm Weighted Probability Distribution Voting (WPDV) is a supervised learning approach to classification. A case which is to be classified is represented as a feature-value pair set: Fcase -- {{fl : Vl},..., {fn :Vn}} An estimation of the probabilities of the various classes for the case in question is then based on the classes observed with similar feature-value pair sets in the training data. To be exact, the probabilit...