Fuzzy Function Support Vector Classifier Results
Study on support vector machine as a classifier
... Results show that PSVM is faster than LSSVM but less accurate than LSSVM. We have formulated NPSVM which implicitly considers the unity norm equality constraints. The non-linear problems are efficiently solved by ...
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Study on proximal support vector machine as a classifier
... proximal support vector machine ...the classifier is a hyperplane in the high-dimensional feature space, it may be nonlinear in the original input ...basis function [4-6] as a kernel ...
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Euler Movement Firefly Algorithm and Fuzzy Kernel Support Vector Machine Classifier for Keystroke Authentication
... SVM classifier and it depends on the information which is shown only through the dot products among the arguments of the ...the classifier and (ii) the kernel operation is subjected to allow the user apply ...
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Ensemble fuzzy support vector machine classifier based on maximum spanning tree for big data analytics
... Today the buzz word in information technology is big data. Classification is one among the thrust research problem in such big data and its corresponding application scenarios. This research work makes use of an ensemble ...
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Fuzzy logic based improved support vector machine (F ISVM) classifier for heart disease classification
... inputs. Fuzzy rule-based classification systems (FRBCSs) (Ishibuchi et ...2011). Support vector machine is one such machine learning algorithm and can be used for classification in data ...mining. ...
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FUZZY BASED SUPPORT VECTOR MACHINE CLASSIFIER WITH WIENER FILTER (FSVM – WF) FOR INTRUSION DETECTION SYSTEM
... proposed classifier is that by identifying new attacks without any difficulty by generating fuzzy rule ...The fuzzy rules are self-generated depending upon the rule’s firing strength and decision ...
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Building Support Vector Machines with Reduced Classifier Complexity
... For many classification problems there exists a small subset of the basis functions 1 suited to the complexity of the problem being solved, irrespective of the training size growth, that will yield pretty much the same ...
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Face Recognition Using Vector Quantization Histogram and Support Vector Machine Classifier
... recognition results are obtained. Fig. 6 shows the recognition results as a function of filter size and ratio of training examples and testing ...
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Intrusion Detection Using Honeypot and Support Vector Machine Classifier
... While the attacker prepares for an attack, the IDS redirects him to the honeypot. We make the attacker believe that he is working with the actual system. The activities related to the attack are recorded by the honeypot ...
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Signature Verification System Based on Support Vector Machine Classifier
... techniques, support vector machines, hidden Markov models. The results show that there are still many challenges in this domain which includes the signatures from the same person are similar but not ...
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Data Perturbation Analysis of the Support Vector Classifier Dual Model
... the support vector classifier dual problem, from which the data perturbation analysis of the corresponding primary problem may be performed through standard re- ...decision function with ...
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Least Squares Support Vector Fuzzy Regression
... the fuzzy regression approaches by Tanaka et ...kernels function, LS_SVFR can denote different type nonlinear regression model to adapt different data ...weight vector and bias term as against the ...
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A Multi classifier Approach to support Coreference Resolution in a Vector Space Model
... dimensional vector space created by applying the SVD technique. The results obtained for the OntoNotes corpus are very good, outperforming the ones obtained by other classifica- tion systems for some ...
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Support Vector Classifier with enhanced feature selection for transient stability evaluation
... Keywords: Transient stability, Support Vector Classifier (SVC), Dimensionality reduction, Feature selection, Energy margin. 1 Introduction Stability problems in power systems are being highly ...
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Support Vector Machine – A Large Margin Classifier to Diagnose Skin Illnesses
... The M. S. University of Baroda, Vadodara, Gujarat State, India - 390 001 Abstract Support Vector Machine (SVM) have been very popular as a large margin classifier due its robust mathematical theory. ...
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Applying a fuzzy classifier to generate Sp ToBI annotation : preliminar results
... Index Terms:Prosodic labeling, fuzzy classifier, Sp ToBI 1. Introduction Prosodic labeling aims to enrich spoken utterances with labels that are representative of the relationship between the prosodic form ...
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An investigation of feature models for music genre classification using the support vector classifier
... 4.1.2 Results & Discussion In each genre 90 out of the 100 music snippets from the training set were randomly selected 10 times to assess the variations in the ...port vector classifier and σ in the ...
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Extending twin support vector machine classifier for multi-category classification problems
... twin support vector machine (OVA-TWSVM) classifiers for multiclass classification ...Experimental results on synthetic datasets and on benchmark datasets from UCI machine learning repository show ...
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Particle swarm optimization for linear support vector machines based classifier selection
... SVM classifier from a set of linear classifiers with the same ...for classifier evaluation based on sum of true positive ratios is proposed together with this algorithm; it is more suitable for imbalanced ...
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Performance Analysis of Classification of Cardiotocograms Using Support Vector Machine based Classifier
... the Support Vector Machine methods with respect to confusion matrix and ...the Support Vector Machine based classification approach provided significant ...the Support Vector ...
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