A Study of a Procedure for Reducing the Feature Set of Workload Data.
MICHIGAN STATE UNIV EAST LANSING DEPT OF COMPUTER SCIENCE
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Workload models are extremely important for computer performance evaluation. The problem of feature reduction for the purpose of the formulation of workload models has received widespread attention. This paper briefly reviews existing schemes for feature selection and reduction, and proposes a feature reduction algorithm based on a linear decision-tree classifier. An example is presented to illustrate the use and validity of this algorithm. Author
- Computer Programming and Software