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46 articles for “Feature Reduction”

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Research ArticleOpen accessIn the abstractFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Independent Rough Set Approach Hybrid with Artificial Bee Colony Algorithm for Dimensionality ReductionNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Dimensionality reduction is viewed as an important pre-processing step for pattern recognition and data mining. As the classical rough set model considers the entire attribute set as a whole to find the subset, comparing all possible combinations of sets of attributes is difficult. Approach: In this study, we have introduced an improved Rough Set-based Attribute Reduction (RSAR) namely … …American Journal of Applied Sciences, Vol. 8, Issue 3 · 25 Mar 2011 · 8,334 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Biometrics Based on Principal Component Analysis and Linear Discriminant AnalysisLih-Heng Chan, Sh-Hussain Salleh, Chee-Ming TingProblem statement: In facial biometrics, face features are used as the required human traits for automatic recognition. Feature extracted from face images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). First, PCA is used for … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,664 accessesView PDFCite
Research ArticleOpen accessIn the abstractVulnerability Assessment of Power System Using Radial Basis Function Neural Network and a New Feature Extraction MethodAhmed M.A. Haidar, Azah Mohamed, Aini HussainVulnerability assessment in power systems is important so as to determine how vulnerable a power system in case of any unforeseen catastrophic events. This paper presents the application of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction (NNWE) for dimensionality reduction of … …American Journal of Applied Sciences, Vol. 5, Issue 6 · 30 Jun 2008 · 7,153 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Recognition Based on Nonlinear Feature ApproachEimad E.A. Abusham, Andrew T.B. Jin, Wong E. Kiong, G. DebashisFeature extraction techniques are widely used to reduce the complexity high dimensional data. Nonlinear feature extraction via Locally Linear Embedding (LLE) has attracted much attention due to their high performance. In this paper, we proposed a novel approach for face recognition to address the challenging task of recognition using integration of nonlinear dimensional reduction Locally Linear Embedding integrated with Local … …American Journal of Applied Sciences, Vol. 5, Issue 5 · 31 May 2008 · 6,520 accessesView PDFCite
Research ArticleOpen accessIn the abstractRotational Linear Discriminant Analysis Using Bayes Rule for Dimensionality ReductionAlok Sharma, Kuldip K. PaliwalLinear discriminant analysis (LDA) finds an orientation that projects high dimensional feature vectors to reduced dimensional feature space in such a way that the overlapping between the classes in this feature space is minimum. This overlapping is usually finite and produces finite classification error which is further minimized by rotational LDA technique. This rotational LDA technique rotates the classes individually … …Journal of Computer Science, Vol. 2, Issue 9 · 30 Sep 2006 · 6,587 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Implementation of Support Vector Machine on the Multi-Label Classification of English-Translated Quranic VersesSatrio Adi Prabowo, Adiwijaya, Mohamad Syahrul Mubarok et al.One of the attempts to understand the meaning and content of the Quran, the central religious text of Islam, is the topic classification of Quranic verses. Verse topic classification aims to help the reader, so he can easily and quickly find information or knowledge contained in the Quran. In this paper, we build a classification model for the topics of … …Journal of Computer Science, Vol. 15, Issue 12 · 19 Dec 2019 · 7,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart Retrofit Solutions of Buildings toward a Low Carbon WorldErdem Cuce, Pinar Mert CuceIn this short communication, energy-efficient, eco-friendly and low-cost solutions for existing buildings are considered in a holistic manner toward low/zero carbon building concept of near future. Buildings are still responsible for about 40% of total primary energy consumption in the world, hence decisive measures need to be taken promptly due to growing significance of environmental issues driven by fossil fuel … …Energy Research Journal, Vol. 9, Issue 1 · 29 Aug 2018 · 7,169 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying EnvironmentSujata G. Bhele, V.H. MankarFace recognition involves matching face images with different environmental conditions. Matching face images with different environmental conditions is not a easy task. Also matching face images considering variations such as changing illumination, pose, facial expression and that with uncontrolled conditions becomes more difficult. This paper focuses on accurately recognizing face images considering all the above variations. The proposed system is … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 3 · 31 Aug 2017 · 8,132 accessesView PDFCite
EditorialOpen accessIn the abstractProtecting crop species from biotic and abiotic constraints in the era of Global Change: are we ready for this challenge?Marco Landi, Giovanni BenelliReliable and affordable supply of food is of crucial importance to the progress and stability of human societies. During the last century, we have assisted to an extraordinary increase of crop yields, especially for the most widespread and consumed crop species, such as rice, wheat, corn and soybean. The Broadbalk experiment, one of the oldest continuous agronomic experiments in the … …American Journal of Agricultural and Biological Sciences, Vol. 11, Issue 2 · 4 Jun 2016 · 8,399 accessesView PDFCite