[PDF] Top 20 Efficient Seizure Classification using Multiclass Support Vector Machine with RFE
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Efficient Seizure Classification using Multiclass Support Vector Machine with RFE
... multi classification scheme based on Support Vector Machine called Hierarchical multi-class support vector machine with a new Extreme Learning Machine kernel is ... See full document
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Bearing Fault Diagnosis using Multiclass Support Vector Machine with efficient Feature Selection Methods
... a support for machinery maintenance ...used Multiclass Support Vector Machines (MSVM) for classifica- tion ...powerful classification tool that is becoming increasingly popular in ... See full document
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Hand Gesture Recognition using Multiclass Support Vector Machine
... An efficient hand gesture recognition system requires higher class robustness, accuracy and ...gestures using Multiclass SVM. There exist many classification algorithms, for example neural ... See full document
5
A Multiclass Sentiment Classification using Skip-Gram Embedding with Support Vector Machine-Stochastic Gradient Descent (SVM-SGD)
... solved using Quadratic Programming (QP) optimisation techniques, thus, multiclass problems determine n ...text classification is the design of effective feature ...sentiment classification ... See full document
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Multiclass Classification with Multi-Prototype Support Vector Machines
... of multiclass SVM able to deal with several prototypes per ...by using a novel efficient optimization procedure within an annealing framework where the energy function corre- sponds to the primal of ... See full document
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OVA Tree Multiclass Framework for Support Vector Machine
... of multiclass classification problems as: recognition of handwritten digits and automatic Speech Recognition ...the machine learning and speech communities for the past few decades due to its ... See full document
6
Optimal Classification of Lung Cancer Related Genes using Enhanced reliefF Algorithm and Multiclass Support Vector Machine
... random forest [10], nearest neighbour classifier [11], etc. Though, the above-mentioned methods have their own limitations such as, consumes more processing time, unable to solve complex technological and scientific ... See full document
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Facial Gesture Recognition using Surface EMG and Multiclass Support Vector Machine (SVM)
... recognition using different machine learning techniques is seen as potential medium in assistive technology and ...feature classification. Finally, statistical features are classified using ... See full document
5
Multiclass Response Feature Selection and Cancer Tumour Classification With Support Vector Machine
... ensured efficient detection of false-positive ...subsets using the above method were further screened for optimality using the Misclassification Error Rates yielded by each of them and their ... See full document
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Document Classification Using Support Vector Machine
... very efficient and reliable classification ...for multiclass classification so it can apply for any number of classes containing news of different ... See full document
5
Multiclass Support Vector Machine with New Kernel for EEG Classification
... in seizure- free intervals, from five patients in the epileptogenic zone (D) and from the hippocampal formation of the opposite hemisphere of the brain ...contains seizure activity, selected from all ... See full document
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Comparison of Classification Algorithms using Machine Learning
... Supervised Learning: In supervised machine learning, a system is trained with data that has been labeled. The labels categories each data point into one or more groups, such as ‘apples’ or ‘oranges’. The system ... See full document
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Brain Tumor Classification using Support Vector Machine
... FEATURE VECTOR GENERATION: Morphological tools are implemented in most advanced image analysis packages. Mathematical morphology is very often used in application where shape of objects and speed is an issue. For ... See full document
6
Development of Mushroom Expert System Based on SVM Classifier and Naive Bayes Classifier
... determined by an orthogonal vector w and a bias b, which defines the points that satisfy . By finding a hyper plane that maximizes the margin of separation q, it is intuitively expected that the classifier will ... See full document
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Malicious Nodes Identification and Classification of Nodes and Detection of UDP Flood Attack with ICMP using OLSR Routing Protocol in MANET Sweta Kriplani, Rupam Kesharwani
... This research also develops the framework for using an attack and protection tree methodology to analyze the security of a MANET. To accomplish this, the structure of attack trees is extended and modified to ... See full document
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Efficient Cluster Based Classification in Big Data Analysis using Support Vector Machine
... to support companies make more useful business decisions by enabling data scientists, predictive modellers and other analytics professionals to analyze large volumes of transaction data, which is impossible to ... See full document
5
Copy move image classification by feature optimization with support vector machine approach
... image classification and recognition.The calculation fuses the classification execution and feature set size into the heuristic guidance, and chooses a feature set with little size and high ... See full document
5
Document Text Classification Using Support Vector Machine
... engineering, machine learning and artificial intelligence focus on the interactions between human's languages and computer machines, by simplicity , how the computers will understand and analyze huge amounts of ... See full document
5
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
22
Automatic Plant Detection Using HOG and LBP Features With SVM
... Texture is a major feature to identify the plants. It describes the surface of the leaf. Backes and Bruno [15] used textural features to classify the plant leaf images. They modeled texture as a surface and multi-scale ... See full document
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