[PDF] Top 20 A Unified View on Multi-class Support Vector Classification
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A Unified View on Multi-class Support Vector Classification
... The LLW, RM, and ATS SVMs rely on a classification calibrated loss function. However, we have shown that a non-classification calibrated training loss function does not need to be a principal problem for an ... See full document
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Multilevel and Multi-class Support Vector Machine based on Affinity Propagation Clustering for Intrusion Detection
... This phase purpose is to pre-process the database file.This phase consists two main steps which are as follows: Firstly, the conversion of the symbolic attributes protocol, service, and flag in numerical is done.The ... See full document
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Classification of EMI discharge sources using time-frequency features and multi class support vector machine
... a vector of 256 descriptive features for 8 ...feature vector dimension from 256 to 59 and improvement in ...for classification, whereas the uniform ones provide information on uniform regions, edges ... See full document
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Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression
... based classification that directly produces probability ...Gini Support Vector Machine (GiniSVM) (Chakrabartty and Cauwenberghs, 2002), a large margin clas- sifier based on a quadratic entropy ... See full document
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AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING
... for classification showed ...on classification of e-mail [19] and classification of fruits based on digital photos processed using Multi Class Support Vector Machine with ... See full document
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Cognitive-Affective Emotion Classification: Comparing Features Extraction Algorithm Classified by Multi-class Support Vector Machine
... or recognition purpose. Two primary processes in face recognition areas are feature extraction and recognition or classification. In the past years, many researchers had used Principal Component Analysis (PCA) or ... See full document
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Utilizing visible and near infrared spectroscopy based on multi-class support vector machines classification to characterize olive oil adulteration
... detection of adulteration is visible/near-infrared (VNIR) spectroscopy. The VNIR spectroscopy, as a cheap and fast method for determining the authenticity and adulteration detection, has shown promising results worldwide ... See full document
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Multi-Class Support Vector Machine Based Continuous Voiced Odia Numerals Recognition
... distribution, so it exhibits poor performance in classification. Therefore, it requires a technique which may be used to classify in a better manner. During last few decades researchers were proposed some ... See full document
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Image Quality Metric Based Intensity Classification With Multi Support Vector Machine
... Multiclass Support Vector Machine aims to allocate labels to instances by exploitation support vector machines, wherever the labels are drawn from a finite set of many ...multiclass ... See full document
5
Multi-Class Support Vector Machine (MSVM) Enabled Indoor Scene Classification With SIFT Features
... the support vector machine (SVM) for the multi-class classification in the adaptive ...proposed multi-class enabled support vector machine (mSVM) has been ... See full document
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Privacy-Preserving Multi-Class Support Vector Machine for Outsourcing the Data Classification in Cloud
... several classification algorithms devel- oped in pattern recognition and machine learning for different applications ...PP classification in literature ( [4]–[7], [29]–[34] and references ...secure ... See full document
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Multiclass Classification with Multi-Prototype Support Vector Machines
... In Section 2 we give some preliminaries and the notation we adopt along the paper. Then, in Section 3 we derive a convex quadratic formulation for the easier problem of learning one prototype per class. The ... See full document
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EMG DIAGNOSIS VIA TIME DOMAIN FEATURES AND BINARY SUPPORT VECTOR MACHINE CLASSIFICATION
... The shapes and firing rates of the motor unit action potentials (MUAPs) in an electromyogram (EMG) signal provide an important source of information for the diagnosis of neuromuscular disorders. In order to extract this ... See full document
5
A fault detection method for railway point systems
... Since the division into 5 folds is done randomly, the accuracy of the classification algorithm given by the cross-validation estimate (equations (10) and (11)) depends on this random division. The best estimate of ... See full document
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Support vector machines for texture classification
... To evaluate the effect of the polynomial degree p on the texture classification performance, a set of experiments was performed with varying degrees of p. The input window size was fixed at 17 17. Table 4 shows ... See full document
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A Novel Approach for MRI Brain Image Classification and Detection
... Feature Extraction: When input data is too large to process, it is transformed in reduce set of features (feature vector). Thus process of transforming an input data in set of feature is called feature extraction ... See full document
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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] ... See full document
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Evaluation of Classification Algorithms with Solutions to Class Imbalance Problem on Bank Marketing Dataset using WEKA
... categorical class label of a data instance, so as to classify it into one of the predetermined ...classes. Class imbalance problem is one of the most important research problem in classification, in ... See full document
8
Copy move image classification by feature optimization with support vector machine approach
... in view of subterranean insect settlement improvement ...image classification and recognition.The calculation fuses the classification execution and feature set size into the heuristic guidance, and ... See full document
5
Shape and Geometric Features-based Semantic Image Retrieval Using Multi-class Support Vector Machine
... The mapping does not impact for the time of learning process since it has dot product and kernel trick. When the number of extracted features is so considerable, the SVMs classifier is a good classifier and vigorous to ... See full document
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