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Multiple Support Vector Machine

Improved support vector machine using multiple SVM-RFE for cancer classification

Improved support vector machine using multiple SVM-RFE for cancer classification

... Abstract— Support Vector Machine (SVM) is a machine learning method and widely used in the area of cancer studies especially in microarray ...proposed Multiple Support ...

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Meta-analytic support vector machine for integrating multiple omics data

Meta-analytic support vector machine for integrating multiple omics data

... In this article, we introduce a meta-analytic framework using the support vector machine. The objective function of Meta-SVM applies the hinge loss and the sparse group lasso, and so we also develop ...

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Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier

Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier

... on support vector machines [4] for developing weather based prediction models of plant diseases is proposed by Rakesh & ...conventional multiple regression, artificial neural network (back ...

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Distributed Support Vector Machine Learning

Distributed Support Vector Machine Learning

... when multiple SVM training rounds are needed as with SVM clustering methods being developed by the Winters-Hilt Group (but not discussed further ...the support feature vectors (SVs) and sometimes some ...

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A HYBRID MODEL FOR CLASSIFYING PLANT STRESSES

A HYBRID MODEL FOR CLASSIFYING PLANT STRESSES

... learning multiple levels of representation to model complex relationships among ...the Support Vector Machine (SVM) is also a proven excellent for binary ...

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Comparative Evaluation of Multiple Linear Regression and Support vector Machine aided Linear and Non

Comparative Evaluation of Multiple Linear Regression and Support vector Machine aided Linear and Non

... method multiple linear regression and support vector machine aided linear method while non-linear QSAR models were developed using Gaussian kernel function aided support vector ...

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Weight Analysis and Prediction of Yak

Weight Analysis and Prediction of Yak

... by multiple linear regression and support vector machine ...the support vector machine is ...the multiple linear regression and the true value is ...the ...

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External Support Vector Machine Clustering

External Support Vector Machine Clustering

... “Bottom-up” hierachical clustering is based on the union between the two nearest cluster. Initially, all data vectors will represent their own cluster, and iteratively clusters will be joined by union to the nearest ...

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Copy move  image classification  by  feature optimization with support  vector machine approach

Copy move image classification by feature optimization with support vector machine approach

... The availability of powerful digital image processing programs, such as Photoshop, makes it relatively easy to create digital forgeries from one or multiple images. An example of a digital forgery is shown in ...

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Heart Disease Prediction and Performance Assessment through Attribute Element Diminution using Machine Learning

Heart Disease Prediction and Performance Assessment through Attribute Element Diminution using Machine Learning

... UCI Machine Learning Repository for predicting the level of heart ...classifier, Support Vector Machine, Kernel Support Vector Machine, Naive Bayes, Random Forest and ...

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A Consistent Information Criterion for Support Vector Machines in Diverging Model Spaces

A Consistent Information Criterion for Support Vector Machines in Diverging Model Spaces

... Information criteria such as AIC (Akaike, 1973) and BIC (Schwarz, 1978) have been used for model selection and their theoretical properties have been well studied, see Shao (1997), Shi and Tsai (2002) and references ...

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Online Full Text

Online Full Text

... methods, support vector machines (SVMs) are well-known [6] by its highly accurate computational capabilities and high-dimensional data ...a vector that consists of a series of scores formed by HMM ...

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Situation prediction of large-scale Internet of Things network security

Situation prediction of large-scale Internet of Things network security

... single machine pro- cessing time spent is almost in a straight line, and the in- crease in the number of nodes in the cluster processing efficiency is also ...

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Traffic Data Analysis using Decision Tree and Naïve Bayes Classifier

Traffic Data Analysis using Decision Tree and Naïve Bayes Classifier

... WEKA is a powerful tool as it contains both supervised and unsupervised learning techniques. WEKA is an efficient approach and outperforms other data mining approaches [7]. We use WEKA because it helps us to evaluate and ...

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Support Vector Machine   Reference Manual

Support Vector Machine Reference Manual

... Option 3 of the SVM parameter menu allows the user to set the free parameters for the SVM (in the pattern recognition case, the size of the upper bound on the Lagrangian variables, i.e. the box constraints, C, and in ...

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Advanced Probabilistic Binary Decision Tree Using SVM for large class problem

Advanced Probabilistic Binary Decision Tree Using SVM for large class problem

... Abstract -In this paper an algorithm of Advanced Probabilistic Binary Decision Tree (APBDT) using SVM for solving large classification problems is introduced, APBDT- SVM is tested in view of the size of the databases. ...

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Robust Multi Weight Vector Projection Support Vector Machine

Robust Multi Weight Vector Projection Support Vector Machine

... decades, Support vector machine (SVM) has gained a great deal of attention due to its great generalization ability, which has been a powerful classification method in the machine learning [1] ...

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Advance Probabilistic Binary Decision Tree using SVM

Advance Probabilistic Binary Decision Tree using SVM

... Mulay et al. [8] propose decision tree based support vector machine which combines support vector machine and decision tree. It is an effective way for solving multi-class ...

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The application of the support vector machine to the classification

The application of the support vector machine to the classification

... Result The misclassification rate of 0.0091 for decision tree and 0.138 for SVM indicate that Support Vector Machine does not perform as well as the decision tree for this set of data 0.[r] ...

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CLASSIFICATION OF ELECTROCARDIOGRAM SIGNALS WITH SUPPORT VECTOR MACHINE AND RELEVANCE VECTOR MACHINE

CLASSIFICATION OF ELECTROCARDIOGRAM SIGNALS WITH SUPPORT VECTOR MACHINE AND RELEVANCE VECTOR MACHINE

... L. Khadra et.al,[3] proposed a high order spectral analysis technique for quantitative analysis and classification of cardiac arrhythmias. The algorithm is based upon bispectral analysis techniques. The bispectrum is ...

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