2011 IEEE 23rd International Conference on Tools with Artificial Intelligence (2011)
Boca Raton, Florida USA
Nov. 7, 2011 to Nov. 9, 2011
Feature selection is an effective technique to reduce the dimensionality of a data set and to select relevant features for the domain problem. Recently, stability of feature selection methods has gained increasing attention. In fact, it has become a crucial factor in determining the goodness of a feature selection algorithm besides the learning performance. In this work, we conduct an extensive experimental study using verity of data sets and different well-known feature selection algorithms in order to study the behavior of these algorithms in terms of the stability.
Feature selection algorithms, stability, dimensionality reduction, data distribution, Jaccard Index, sample size
H. Liu, S. Alelyani and L. Wang, "The Effect of the Characteristics of the Dataset on the Selection Stability," 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence(ICTAI), Boca Raton, Florida USA, 2011, pp. 970-977.