Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Motion segmentation using feature correspondences can be regarded as a combinatorial problem. A motion segmentation algorithm using feature selection and subspace method is propos...
Identifying a subset of features that preserves classification accuracy is a problem of growing importance, because of the increasing size and dimensionality of real-world data se...
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...