In this paper, we compare the performance of Intrusion Detection System Classifiers using various feature reduction techniques. To enhance the learning capabilities and reduce the computational intensity of competitive learning neural network classifiers, different dimension reduction techniques have been proposed. These include: Principal Component Analysis, Linear Discriminant Analysis, Indep...

Faces-classes of grains, often referred to as topological features, largely dictate the evolution polycrystalline microstructures during grain growth. Realising these features is generally an arduous task, demanding sophisticated techniques. In present work, a distinct machine-learning algorithm extended for first time comprehend distribution grains constituting continuum. This regression-based...