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72 articles for “Support Vector Machine Algorithm”
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Research ArticleOpen accessIn the abstractCancer Classification using Support Vector Machines and Relevance Vector Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The objective of this study is, to find the smallest set of genes that can ensure highly accurate classification of cancer from micro array data by using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: The computational burden and noise arising from irrelevant genes are much reduced; the cost for cancer testing … …Journal of Computer Science, Vol. 7, Issue 9 · 25 Jul 2011 · 7,593 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Image Retrieval using Novel Gaussian Fuzzy Feed Forward-Neural NetworkC. Ramesh Babu Durai, V. DuraisamyProblem statement: With extensive digitization of images, diagrams and paintings, traditional keyword based search has been found to be inefficient for retrieval of the required data. Content-Based Image Retrieval (CBIR) system responds to image queries as input and relies on image content, using techniques from computer vision and image processing to interpret and understand it, while using techniques from information … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,326 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Behavior Classification Using Multi-Class Relevance Vector MachineB. Yogameena, S. Veera Lakshmi, M. Archana, S. Raju AbhaikumarProblem statement: In computer vision and robotics, one of the typical tasks is to identify specific objects in an image and to determine each object’s position and orientation relative to coordinate system. This study presented a Multi-class Relevance Vector machine (RVM) classification algorithm which classifies different human poses from a single stationary camera for video surveillance applications. Approach: First the … …Journal of Computer Science, Vol. 6, Issue 9 · 30 Sep 2010 · 7,390 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Survey of Protein Fold Recognition AlgorithmsMohammed Said Abual-Rub, Rosni AbdullahProblem statement: Predicting the tertiary structure of proteins from their linear sequence is really a big challenge in biology. This challenge is related to the fact that the traditional computational methods are not powerful enough to search for the correct structure in the huge conformational space. This inadequate capability of the computational methods, however, is a major obstacle in facing … …Journal of Computer Science, Vol. 4, Issue 9 · 30 Sep 2008 · 6,877 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,695 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordHuman Age Predication from Face Images Based on Combining Deep Wavelet Network and Machine Learning AlgorithmsZahraa Salam Abu Ghrban, Nidhal K. EL AbbadiDue to the numerous variances in face appearance, age estimation using facial images is a difficult subject. Many factors can affect the estimation of human age such as race, face post, gender, lifestyle, etc. By considering more factors, the optimum performance may be obtained. In this study, we proposed a method to predict the age of facial images. The proposed … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 5,568 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,788 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,435 accessesView PDFCite