One class support vector machine
Burned area mapping in the brazilian savanna using a one-class support vector machine trained by active fires
... a One-Class Support Vector Machine for burned area mapping, and applied the resulting classification algorithm to 300-m spatial resolution imagery from the Project for On-Board ...
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A NOVEL MULTICLASS SUPPORT VECTOR MACHINE ALGORITHM USING MEAN REVERSION AND COEFFICIENT OF VARIANCE
... building one SVM per class and trains it while the rest of the training data remains as the other class so-called ...‘One’ class is flexible depending upon the structure of datasets and ...
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Specific Land Cover Class Mapping by Semi-Supervised Weighted Support Vector Machines
... and one-class learning algorithms ...where one seeks to separate the classes of interest from all irrelevant classes ...in machine learning research, and has been shown to perform well in most ...
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Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): an algorithm for joint optimization of discrimination and calibration.
... their class memberships, the prediction task is often modeled by supervised learning algorithms, which aim at finding an optimal mapping between features and outcomes (usually represented by the zero-one ...
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Integrated Features by Administering the Support Vector Machine (SVM) of Translational Initiations Sites in Alternative Polymorphic Contex
... Support Vector Machine (SVM) and kernel-based methods have been studied extensively to several of pattern classification ...contains one target value (i.e. the class labels) and several ...
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Support vector machine ensemble based on feature and hyperparameter variation
... negative class examples are usually much more common than posi- tive ...positive class ωpos is set to ...and one, the X-Y point traces the ROC curve and a high area under it indicates an accurate ...
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An Efficient Skin Cancer Diagnostic System Using Bendlet Transform and Support Vector Machine
... More information about SVM can be found in (Cortes & Vapnik 1995). The classification system is implemented with the help of dermoscopic images in PH2 database. This database comprises of three classes of dermoscopic ...
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EMG Diagnosis via AR Modeling and Binary Support Vector Machine Classification
... A binary SVM classifier is used in this work for classification of clustered MUAPs into NOR, MYO and MND classes [23], [24]. A classification task based on SVM usually involves training and testing data, which consist of ...
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A multi-label learning based kernel automatic recommendation method for support vector machine.
... stored support vectors or training time complexity ...with one special kernel function is rational. Moreover, the issue of class imbal- ance distribution often exists in real-world applications, in ...
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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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Classifying Cyst and Tumor Lesion Using Support Vector Machine Based on Dental Panoramic Images Texture Features
... use one third hold out cross validation of 133 data images by randomly selecting 94 images referring to each class as data training, while the rest (39 images) as the data ...
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Mammalian microRNA prediction through a support vector machine model of sequence and structure.
... abundant class of ,22 nt long endogenous non-protein-coding RNAs that function by binding to target sites on 39-UTRs of messenger RNAs (mRNAs) to repress translation or mediate mRNA degradation (reviewed in ...
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Fire Detection Using Support Vector Machine in Wireless Sensor Network and Rescue Using Pervasive Devices
... factors. One of the causes is smokes during the massive ...possibility Support Vector Machine (SVM) for detecting the Fire which has large data ...the Support Vector ...
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Weighted Twin Support Vector Machine with Universum
... to one class and is as far as possible from the other one [9] ...large one, makes the learning speed of TSVM approximately four times faster than the standard ...Twin Support ...
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Plant microRNA-target interaction identification model based on the integration of prediction tools and support vector machine.
... and machine learning ...introduce machine learning ...ones. Machine learning approaches have already been employed in animal miRNA targets prediction successfully, such as miTarget [20], GenMiR++ ...
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Support Vector Machines na previsão do comportamento de uma ETAR
... (1996a) refere que o DM consiste numa das fases do processo KDD. A fase inicial consiste na seleção de dados, que inclui a aprendizagem do domínio da aplicação e a escolha do conjunto d[r] ...
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Bagging Support Vector Machines for Leukemia Classification
... In this study, we used majority voting aggregation technique due to its simplicity and popularity. Majority voting selects the class label that achieves the highest number of vote from each SVM models. Least ...
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Off-line signature verification based on hus moment invariants and zone features using support vector machine
... Reducing the width of signature image to a single black pixel or reducing the connected region in the image to a smaller size and minimum cross-sectional width character is called thinning. By thinning we can remove the ...
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Morphological analysis of dendrites and spines by hybridization of ridge detection with twin support vector machine
... Dendritic spines are described as neuronal protrusions. The morphology of dendritic spines and dendrites has a strong relationship to its function, as well as playing an important role in understanding brain function. ...
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Support vector machines and kernels for computational biology.
... Normalization. Large margin classifiers are known to be sensitive to the way features are scaled (see, for example [42], in the context of SVMs). It can therefore be essential to normalize the data. This observation ...
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