We present an approach to modeling the average case behavior of learning algorithms. Our motivation is to predict the expected accuracy of learning algorithms as a function of the...
Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that descri...
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
- The problem of estimating the energy consumption at register transfer level is addressed from an information theoretical point of view. It is shown that the average switching act...
The quality of software measurement data affects the accuracy of project manager’s decision making using estimation or prediction models and the understanding of real project st...