Multichannel Gabor filters (MGFs) and Markov random fields (MRFs) are two common methods for texture classification. However, the two above methods make the implicit assumption that textures are acquired in the same viewpoint, which is unsuitable for rotation-invariant texture classification. In this paper, rotation-invariant (RI) texture features are developed based on MGF and MRF. A novel alg...

We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis (ICA). Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to cl...

This work tackles the problem of selecting a subset of features in an inductive learning setting, by introducing a novel Thermodynamic Feature Selection algorithm (TFS). Given a suitable objective function, the algorithm makes uses of a specially designed form of simulated annealing to find a subset of attributes that maximizes the objective function. The new algorithm is evaluated against one ...

A survey study about the various methods of feature recognition with machine learning for affective computing is examined. In order to explore the methods of feature recognition with machine learning methods, Sequential Floating Forward Selection (SFFS), Minimum Redundancy – Maximum Relevance (mRMR), Information Gain(IG), and Fisher projection (FP) are discussed. As the machine learning methods...

A new suboptimal search strategy suitable for feature selection in very high-dimensional remote sensing images (e.g., those acquired by hyperspectral sensors) is proposed. Each solution of the feature selection problem is represented as a binary string that indicates which features are selected and which are disregarded. In turn, each binary string corresponds to a point of a multidimensional b...

Experiment 2: TCS images were obtained by Philips SONOS 5500 with different examiners. Totally, 67 images from 38 PD patients and 71 images from 39 healthy subjects were included. All 77 subjects underwent a neurological examination. The rotationinvariant Gabor filter bank was applied to the ROI of TCS images. Then the Gabor features, mean, std and entropy, were calculated and evaluated by SVMs...

Abstract Aiming at the characteristics of a long short-term memory network (LSTM) which is suitable for processing high-dimensional, strongly coupled, and highly time-dependent data, it combines advantages feature selection to reduce difficulty learning tasks improve performance model fault diagnosis. This paper proposes an LSTM method combining sequential floating forward search with integrate...

Feature subset selection (FSS) has been an active area of research in machine learning. A number of techniques have been developed for selecting an optimal or sub-optimal subset of features, because it is a major factor to determine the performance of a machine-learning technique. In this paper, we propose and develop a novel optimization technique, namely, a binary coordinate ascent (BCA) algo...

In this paper, two strategies to compute the support sets system for the supervised classifier ALVOT (voting algorithms) using sequential floating selection are presented. ALVOT is a supervised classification model based on the partial precedence principle, therefore, it needs, as feature selection, a set of features subsets, this set is called support sets system. The sequential floating selec...