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50 results for “support vector machines”
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Research ArticleOpen accessIn the abstractSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,114 accessesView PDFCite
Review ArticleOpen accessIn the abstractProtein Sequences Features Extraction for Predicting Beta- Turns and their Types: A ReviewMurtada Khalafallah Elbashir ElfakiBeta-turns are considered to be important secondary structure types that have essential role in molecular recognition, protein folding and stability. They represent 25% of protein structures, therefore they are the most common type of non-repetitive or tight turns structures. Their prediction is considered to be an important issue in bioinformatics and molecular biology, because it provides valuable information and inputs … …Journal of Computer Science, Vol. 15, Issue 9 · 1 Oct 2019 · 7,694 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector MachineLekini Nkodo Claude Bernard, Ndzana Benoît, Oumarou HamandjodaNon-Technical Losses (NTLs) in the Cameroonians electricity network are approximately 30 to 40% of production and are estimated at several billion CFA francs per year for National Electricity Company (ENEO); Hence the importance of finding effective solutions to fight against these losses. The purpose of this work was to develop a tool for the fraud detection for Cameroon National Electricity … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 6 Jan 2017 · 7,544 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Classification Techniques on Fused Optical and SAR Images for Shoreline Extraction: A Case Study at Northeast Coast of Peninsular MalaysiaSyaifulnizam Abd Manaf, Norwati Mustapha, Md Nasir Sulaiman et al.Shoreline is a very important element to identify exact boundary at the coastal areas of a country. However, in order to identify land-water boundary for a large region using traditional ground survey technique is very time consuming. Alternatively, shoreline can be extracted by using satellite images that minimizes the mapping errors. The trend of extracting shoreline has been shifted from … …Journal of Computer Science, Vol. 12, Issue 8 · 27 Oct 2016 · 7,708 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPEECH/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 · 6,841 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid of Fuzzy Clustering Neural Network Over NSL Dataset for Intrusion Detection SystemDahlia Asyiqin Ahmad Zainaddin, Zurina Mohd HanapiIntrusion Detection System (IDS) is one of the component that take part in the system defence, to identify abnormal activities happening in the computer system. Nowadays, IDS facing composite demands to defeat modern attack activities from damaging the computer systems. Anomaly-Based IDS examines ongoing traffic, activity, transactions and behavior in order to identify intrusions by detecting anomalies. These technique identifies … …Journal of Computer Science, Vol. 9, Issue 3 · 4 May 2013 · 6,574 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Local Network Intrusion Detection System Based on Support Vector MachineMuamer N. Mohammad, Norrozila Sulaiman, Emad T. KhalafProblem statement: Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable Intrusion Detection Systems (IDS). Many methods and techniques were used for modeling the IDS, but some of them contribute little or not to resolve it. Approach: Intrusion detection system for local area network by using Support Vector Machines (SVM) was … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 7,313 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnbalance Quantitative Structure Activity Relationship Problem Reduction in Drug DesignD. Pugazhenthi, S. P. RajagopalanProblem statement: Activities of drug molecules can be predicted by Quantitative Structure Activity Relationship (QSAR) models, which overcome the disadvantage of high cost and long cycle by employing traditional experimental methods. With the fact that number of drug molecules with positive activity is rather fewer than that with negatives, it is important to predict molecular activities considering such an unbalanced … …Journal of Computer Science, Vol. 5, Issue 10 · 31 Oct 2009 · 6,704 accessesView PDFCite
Research ArticleOpen accessIn the abstractChi Square Feature Extraction Based Svms Arabic Language Text Categorization SystemAbdelwadood Moh’d A MESLEHThis paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system shows a high classification effectiveness for Arabic data set in term of F-measure … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 11,057 accessesView PDFCite