In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
There is an increasing interest in techniques that support measurement and analysis of fielded software systems. One of the main goals of these techniques is to better understand ...
Murali Haran, Alan F. Karr, Alessandro Orso, Adam ...
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
The Sensitivity-Based Linear Learning Method (SBLLM) is a learning method for two-layer feedforward neural networks, based on sensitivity analysis, that calculates the weights by s...
Three factors are related in analyses of performance curves such as learning curves: the amount of training, the learning algorithm, and performance. Often we want to know whether...
Justus H. Piater, Paul R. Cohen, Xiaoqin Zhang, Mi...