Title :
The Effect of the Characteristics of the Dataset on the Selection Stability
Author :
Alelyani, Salem ; Liu, Huan ; Wang, Lei
Author_Institution :
Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA
Abstract :
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.
Keywords :
data mining; learning (artificial intelligence); data set dimensionality; feature selection stability; learning performance; Biological system modeling; Correlation; Indexes; Prediction algorithms; Robustness; Stability criteria; Feature selection algorithms; Jaccard Index; data distribution; dimensionality reduction; sample size; stability;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Conference_Location :
Boca Raton, FL
Print_ISBN :
978-1-4577-2068-0
Electronic_ISBN :
1082-3409
DOI :
10.1109/ICTAI.2011.167