Abstract. Feature selection is an important task in data mining because it allows to reduce the data dimensionality and eliminates the noisy variables. Traditionally, feature selec...
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in hig...
Information networks are widely used to characterize the relationships between data items such as text documents. Many important retrieval and mining tasks rely on ranking the dat...