At the present, several applications need to classify high dimensional points belonging to highly unbalanced classes. Unfortunately, when the training set cardinality is small compared to the data dimensionality (‘‘small sample size’’ problem) the classification performance of several well-known classifiers strongly decreases. Similarly, the classification accuracy of several discriminative met...

This paper presents a hybrid approach to face-feature extraction based on the trace transform and the novel kernel partial-least-squares discriminant analysis (KPA). The hybrid approach, called trace kernel partial-least-squares discriminant analysis (TKPA) first uses a set of fifteen trace functionals to derive robust and discriminative facial features and then applies the KPA method to reduce...

Ancient glass artifacts are highly susceptible to weathering in burial environments, which can cause changes their chemical composition. To address the problem of identifying and analysing composition ancient artifacts, this paper proposes a classification identification model based on Fisher discriminant method. Firstly, considering that proportion components change during process, affect corr...

Kernel Fisher discriminant analysis (KFD) is an effective method to extract nonlinear discriminant features of input data using the kernel trick. However, conventional KFD algorithms endure the kernel selection problem as well as the singular problem. In order to overcome these limitations, a novel nonlinear feature extraction method called adaptive quasiconformal kernel Fisher discriminant ana...

this article is for the coupling fault diagnosis of rotor system, and does in-depth analysis of the rotor unbalance and misalignment, and the fault formed by the coupling of these two. Through research, Rotor Coupling was found filled with rich features. In this paper, Wavelet packet de-noising ideas being introduced to the local Fisher discriminant analysis (LFDA), a new method of fault diagno...

In this paper, a novel discriminant analysis method for a Gabor-based image feature extraction and representation is proposed and then implemented. The horizontal and vertical two-dimensional principal component analysis (HV-2DPCA) is directly applied to a Gabor face to reduce the redundant information and preserve a bi-directional characteristic as well. It is followed by an enhanced Fisher li...