An iterative model selection algorithm is proposed. The algorithm seeks relevant features and an optimal number of codewords (or codebook size) as part of the optimization. We use...
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Product line engineering allows for the rapid development of variants of a domain specific application by using a common set of reusable assets often known as core assets. Variabil...
: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...