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Maximum scatter difference (MSD) discriminant criterion was a recently presented binary discriminant criterion for pattern classification that utilizes the generalized scatter difference rather than the generalized Rayleigh quotient as a class separability measure, thereby avoiding the singularity problem when addressing small-sample-size problems. MSD(More)
In this paper we propose a novel feature selection method based on linear discriminant analysis (LDA). To view feature selection as a numerical computation problem, the paper shows, for the first time, that it is feasible to employ LDA for feature selection. The proposed method also shows that different components statistically have different effects on the(More)
Anomaly detection has emerged as an important technique in many application areas mainly for network security. Anomaly detection based on machine learning algorithms considered as the classification problem on the network data has been presented here. Dimensionality reduction and classification algorithms are explored and evaluated using KDD99 dataset for(More)
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