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119 results for “Support Vector Machine (SVM)”
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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 · 8,119 accessesView PDFCite
Research ArticleOpen accessIn the abstractUltimate Prediction of Stock Market Price MovementRebwar M. Nabi, Soran Ab. M. Saeed, Habibolah Bin Harron, Hamido FujitaInvestment in the stock market is currently very popular due to its economic gain. Numerous researchers’ and academicians’ work is focused on financial time series prediction due to its data availability and profitability. Therefore, this study presents the design and implementation of a novel binary classification framework to predict stock market trends. The framework is composed of data preprocessing, feature … …Journal of Computer Science, Vol. 15, Issue 12 · 25 Dec 2019 · 8,549 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 · 7,793 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Neuromuscular Diseases Using Complexity of Electromyogram SignalsKawser Ahammed, Mosabber Uddin AhmedCharacterization of Electromyogram (EMG) signals is important for identifying neuromuscular diseases. Although various techniques were implemented for classification, none of them were implemented in the complexity domain. In this study, characterization of EMG signals recorded from healthy, neuropathic and myopathic subjects has been performed in complexity domain based on Multiscale Entropy (MSE) method. To do this, the multiscale entropy method … …Neuroscience International, Vol. 10, Issue 1 · 7 Dec 2019 · 7,935 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 · 7,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifying and Predicting Students’ Performance using Improved Decision Tree C4.5 in Higher Education InstitutesMohammed Hikmat Sadiq, Nawzat Sadiq AhmedStudents’ information in higher education institutions increases yearly. It is hard for them to extract meaningful information from the huge amount of data manually. Such information can support academic staff to stop students from dropping out at the end of courses. This can be done by evaluating the students’ performance for the course and also by predicting their performance in … …Journal of Computer Science, Vol. 15, Issue 9 · 12 Sep 2019 · 9,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractCost-based Reweighting for Principal Lq Support Vector Machines for Sufficient Dimension ReductionAndreas ArtemiouIn this work we try to address the imbalance of the number of points which naturally occurs when slicing the response in Sufficient Dimension Reduction methods (SDR). Specifically, some recently proposed support vector machine based (SVM-based) methodology suffers a lot more due to the properties of the SVM algorithm. We target a recently proposed algorithm called Principal LqSVM and we … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 5 Sep 2019 · 7,260 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn IoT based House Intruder Detection and Alert System using Histogram of Oriented GradientsNico Surantha, Wingky R. WicaksonoThis research aims to design and implement a home security system with human detection capability. Traditional home security systems, i.e., Closed-Circuit Television (CCTV) can only capture and record videos without the ability of giving warning feedback if there is any suspicious object. Therefore, an additional object detection and warning method is required. The proposed design is implemented using Raspberry Pi … …Journal of Computer Science, Vol. 15, Issue 8 · 8 Aug 2019 · 9,222 accessesView PDFCite
Research ArticleOpen accessIn the abstractObject Detection and Classification from Thermal Images Using Region based Convolutional Neural NetworkUsha Mittal, Sonal Srivastava, Priyanka ChawlaIn recent years, object detection and classification has gained so much popularity in different application areas like face detection, self- driving cars, pedestrian detection, security surveillance systems etc. The traditional detection methods like background subtraction, Gaussian Mixture Model (GMM), Support Vector Machine (SVM) have certain drawbacks like overlapping of objects, distortion due to smoke, fog, lightening conditions etc. In this … …Journal of Computer Science, Vol. 15, Issue 7 · 18 Jul 2019 · 9,454 accessesView PDFCite
Research ArticleOpen accessIn the abstractDimensionality Reduction using Principal Component Analysis for Cancer Detection based on Microarray Data ClassificationAdiwijaya, Untari N. Wisesty, E. Lisnawati et al.Cancer is one of the most deadly diseases in the world. The International Agency for Research on Cancer (IARC) noted 14.1 million new cancer cases and 8.2 million deaths from cancer in 2012. In the last few years, DNA microarray technology has increasingly been used to analyze and diagnose cancer. Analysis of gene expression data in the form of microarray … …Journal of Computer Science, Vol. 14, Issue 11 · 15 Nov 2018 · 9,938 accessesView PDFCite