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170 results for “SVM”
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Research ArticleOpen accessIn the keywordsFractal Dimension for Lung Sound Classification in Multiscale SchemeAchmad Rizal, Risanuri Hidayat, Hanung Adi NugrohoLung sound is a biological signal with the information of respiratory system health. Health lung sound can be differentiated from other pathological sounds by auscultation. This difference can be objectively analyzed by a number of digital signal processing techniques. One method in analyzing the lung sound is signal complexity analysis using fractal dimension. To improve the accuracy of lung sound … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 9,289 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSentiment Analysis: Comparative Study between GSVM and KNNHany Mohamed, Ayman Atia, Mostafa-Sami M. MostafaSentiment classification aims detecting general opinion of users in social media towards business products or daily life events. The classification tells whether sentiment is positive or negative. Techniques of sentiment classification are categorized into lexical analysis and machine learning techniques. In this paper, we propose a comparative study between SVM applied genetics (GSVM) against KNN algorithm in terms of speed … …American Journal of Applied Sciences, Vol. 15, Issue 6 · 1 Aug 2018 · 8,363 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUnfair Reviews Detection on Amazon Reviews using Sentiment Analysis with Supervised Learning TechniquesElshrif Ibrahim Elmurngi, Abdelouahed GherbiReputation and trust are significantly important and play a pivotal role in enabling multiple parties to establish relationships that achieve mutual benefit especially in an E-Commerce (EC) environment. There are several factors negatively affecting the sight of customers and sellers in terms of reputation. For instance, lack of credibility in providing feedback reviews, by which users might create phantom feedback … …Journal of Computer Science, Vol. 14, Issue 5 · 14 May 2018 · 9,889 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparison Between Selective Sampling and Random Undersampling for Classification of Customer Defection Using Support Vector MachineHeri Kuswanto, Yogi Sarumaha, Hayato OhwadaQuality of a product determines the customer loyalty and it can be measured by conducting a survey. Company ‘X’ that sells three kinds of product (low, medium and high price) collected very large dataset through an online survey and recorded customer defection and their characteristic. The measured variables are Update Accumulation, Product Price, Customer Type, Delivery Status and Customer Defection. … …Journal of Computer Science, Vol. 13, Issue 8 · 16 Aug 2017 · 7,272 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,141 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCombining SURF and MSER along with Color Features for Image Retrieval System Based on Bag of Visual WordsHeba A. ElnemrContent-Based Image Retrieval (CBIR) has received an extensive attention from researchers due to the rapid growing and widespread of image databases. Despite the massive research efforts consumed for CBIR, the completely satisfactory results have not yet been attained. In this article, we offer a new CBIR technique that relies on extracting Speeded Up Robust Features (SURF) and Maximally Stable Extremal … …Journal of Computer Science, Vol. 12, Issue 4 · 9 May 2016 · 7,709 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBRAIN TUMOR CLASSIFICATION BASED ON CLUSTERED DISCRETE COSINE TRANSFORM IN COMPRESSED DOMAINV. Anitha, S. MurugavalliThis study presents a novel method to classify the brain tumors by means of efficient and integrated methods so as to increase the classification accuracy. In conventional systems, the problem being the same to extract the feature sets from the database and classify tumors based on the features sets. The main idea in plethora of earlier researches related to any … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,537 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFAULT DETECTION IN SWITCHED RELUCTANCE MOTOR DRIVES USING DISCRETE WAVELET TRANSFORM AND K-MEANS CLUSTERINGV. S. Chandrika, A. Ebenezer JeyakumarThis study presents a novel method of detection of inter turn shorts based on k means clustering technique. In addition to inter turn short detection, the other faults like open, short, phase to phase faults and DC volt-age faults are detected through wavelet transforms and k means clustering. Open and short faults are classified using artificial neural network. All other … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 30 Dec 2013 · 7,990 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSPEECH/MUSIC CLASSIFICATION USING WAVELET BASED FEATURE EXTRACTION TECHNIQUESThiruvengatanadhan Ramalingam, P. DhanalakshmiAudio classification serves as the fundamental step towards the rapid growth in audio data volume. Due to the increasing size of the multimedia sources speech and music classification is one of the most important issues for multimedia information retrieval. In this work a speech/music discrimination system is developed which utilizes the Discrete Wavelet Transform (DWT) as the acoustic feature. Multi … …Journal of Computer Science, Vol. 10, Issue 1 · 8 Nov 2013 · 6,846 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Adaptive Region Growing Algorithm with Support Vector Machine Classifier for Tuberculosis Cavity IdentificationK. Meenakshi Sundaram, C. S. RavichandranThe major world health menace is Tuberculosis (TB) that has the effect on one-third of the global population and millions of new infections are occurring every year. The cavities in the upper lung zone are a strong indicator that the disease has developed into a highly contagious state. The study includes 52 Chest X-ray images with Tuberculosis and 43 Chest … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 29 Oct 2013 · 7,073 accessesView PDFCite