Support Vector Machine
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 experiments are conducted on the proposed computer-aided diagnosis systems with the help of lung images obtained from the reputed hospital. This experimentation data consists of 1000 lung images. Those 1000 lung ...
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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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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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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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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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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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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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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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An Approach with Support Vector Machine using Variable Features Selection on Breast Cancer Prognosis
... The support vector machine is originally a binary classification method developed by Vapnik ...the support vector algorithm simply looks for the separating hyperplane with the biggest ...
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Weighted Twin Support Vector Machine with Universum
... machine (TSVM) classifier for binary classification. TSVM generates two nonparallel hyper-planes by solving two small QPPs such that each hyperplane is closer to one class and is as far as possible from the 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 MULTICLASS SUPPORT VECTOR MACHINE ALGORITHM USING MEAN REVERSION AND COEFFICIENT OF VARIANCE
... We also selected the Holdout model, which is part of the model evaluation used to segregate training and test datasets, before partitioning them using the mean reve[r] ...
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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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Fruit recognition and classification based on SVM method for production prediction of peaches
... The concept of Precision Agriculture is usually associated with the usage of high-end technology equipment (hardware or software) to evaluate or monitor the conditions of a determined portion of land, adjusting ...
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MRI pattern recognition in multiple sclerosis normal-appearing brain areas.
... linear Support Vector Machine algorithm was used in multiple local classification analyses to determine the diagnostic accuracy in separating MS patients from healthy controls based on voxel tissue ...
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