support vector machine (SVM)
A multi-label learning based kernel automatic recommendation method for support vector machine.
... with Support Vector ...of support vectors and the CPU time of SVM with different ...feature vector of data characteristics and identifying the corre- sponding applicable kernel ...
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A Computer Aided Diagnosis System for Lung Cancer Detection Using Support Vector Machine
... The initial stage of the proposed technique is lung region extraction using several image processing techniques. The second stage is segmentation (Armatur et al., 1992) of extracted lung region using Fuzzy Possibilistic ...
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Fire Detection Using Support Vector Machine in Wireless Sensor Network and Rescue Using Pervasive Devices
... A Support Vector Machine (SVM) performs classification by constructing an N-dimensional hyper plane that optimally separates the data into two ...categories. Support Vector ...
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Classification of Brain Tumor Using Support Vector Machine Classfiers
... Approaches used for classification falls into two categories. First category is supervised learning technique such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and K-Nearest ...
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APLICAÇÃO DO ALGORITMO SUPPORT VECTOR MACHINE NA ANÁLISE ESPAÇO-TEMPORAL DO USO E OCUPAÇÃO DO SOLO NA BACIA DO RIO VIEIRA
... O mapeamento do uso e cobertura do solo permite a obtenção de informações que fomentam a construção de cenários ambientais e indicadores, como subsídios da avaliação da capacidade de suporte ambiental, sendo este ...
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EMG Diagnosis via AR Modeling and Binary Support Vector Machine Classification
... There are more than 100 neuromuscular disorders that affect the brain, spinal cord, nerves and muscles. Many of these diseases are hereditary and life expectancy of many sufferers is considerably reduced. Early detection ...
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Slope Deformation Prediction Based on Support Vector Machine
... SVM(support vector machine) is classification and regression method developed on the basis of statistical ...theory. Support vector machine improves the generalization capability ...
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Off-Line Signature Authentication Based on Moment Invariants Using Support Vector Machine
... 2002). Support vector machine maps the input vectors into a high dimensional feature space through nonlinear ...searched. Support Vector Machine (SVM) is very effective method ...
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lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.
... Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biologi- cal study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones ...
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An Approach with Support Vector Machine using Variable Features Selection on Breast Cancer Prognosis
... of machine learning. In this paper we have used an approach by using support vector machine classifier to construct a model that is useful for the breast cancer survivability ...other ...
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Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals
... of machine learning-based pattern recognition techniques in different neuropsychiatric ...The support vector machine (SVM) is a multivariate machine learning approach for classifying ...
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A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine.
... For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic ...
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Weighted Twin Support Vector Machine with Universum
... concerned. Support Vector Machine with Universum ( �-SVM) is a new algorithm, which can exploit Universum samples to improve the classification performance of ...Twin Support Vector ...
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Comparison of support vector machine and object based classification methods for coastline detection
... Maiti, S. and Bhattacharya, A.K., 2009. Shoreline change analysis and its application to prediction: A remote sensing and statistics based approach, Marine Geology, 257, 11–23. Song, X., Duan, Z., Jiang, X., 2012. ...
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A novel support vector machine-based approach for rare variant detection.
... Advances in next-generation sequencing technologies have enabled the identification of multiple rare single nucleotide polymorphisms involved in diseases or traits. Several strategies for identifying rare variants that ...
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Mammalian microRNA prediction through a support vector machine model of sequence and structure.
... three support vector machine models sequentially to discover new miRNA candidates in mammalian genomes based on sequence, secondary structure, and ...
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Feature Extraction based Approaches for Improving the Performance of Intrusion Detection Systems
... Abstract —In recent years, the rapid development of information and communication technology results in too many loopholes in the network, and thus attracts lots of hackers’ attacks. Intrusion Detection System (IDS) has ...
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MULTI-LABEL CLASSIFICATION OF PRODUCT REVIEWS USING STRUCTURED SVM
... With the rapid growth of technology and its applications, text data has become one of the important information sources in real world scenarios. In such a scenario, text classification plays an important role in ...
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Surface Electromyography-Based Facial Expression Recognition in Bi-Polar Configuration
... Abstract: Problem statement: Facial expression recognition has been improved recently and it has become a significant issue in diagnostic and medical fields, particularly in the areas of assistive technology and ...
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Specific Land Cover Class Mapping by Semi-Supervised Weighted Support Vector Machines
... in machine learning research, and has been shown to perform well in most multi-class problems ...multi-class support vector machine (SVM) showing better generalisation ability than other ...
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