GA-based feature selection
An ELM Wrapped GA based multiobjective feature selection for identifying cancer microRNA markers
... multiobjective GA-based feature selection approach wrapped with ELM classifier has been formulated for identification of miRNA markers from miRNA expression ...literatures. Based on the ...
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Classification of Normal and Pathological Voice using GA and SVM
... a feature set, so as to detect voice disorders in children based on which further treatments can be prescribed by a ...(GA) based feature selection is utilized to select best set ...
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A Genetic Algorithm-Based Feature Selection
... the GA-FS in this work, the resuts of the GA-based features were compared with a number of WEKA-Based features and test were also made using the selected features on a number of WEKA ...
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A new genetic algorithm for multi-label correlation-based feature selection.
... for feature selection [15,16,17] – is to reduce the number of features given as input to the GA when the number of features is very large, to reduce the processing time and improve the scalability of ...
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Feature Selection Based On Hybrid Genetic Algorithm With Support Vector Machine (GA-SVM)
... KNN is an instance-based classifier, which works on the assumption that classification of unknown instances can be identified by relating the unknown to the known instances according to some distance or similarity ...
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Genetic Algorithm (GA) Implementation for Feature Selection in Manipuri POS Tagging
... Rule-based based in (Brill, 1992). Also a transformation-based error-driven learning based POS tagger in (Brill, 1995), maxi- mum entropy methods based POS tagger in (Rat- naparakhi, ...
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Intelligent emotion recognition from facial and whole-body expressions using adaptive ensemble models
... space based on their whole-body ...conduct feature selection and identify their most optimal discriminative combinations for affective dimensional ...method based on inter-annotator ...
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Random forest based optimal feature selection for partial discharge pattern recognition in HV cables
... categories, feature selection is conducive to removal of the redundant and irrelevant features and to reduction of the computational complexity of the algorithm ...[8]. Feature selection ...
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Development of Spectral Disease Indices for ‘Flavescence Dorée’ Grapevine Disease Identification
... in GA, chromosomes are the bit strings (individuals that form the population), gene is the feature ...the feature indexed by the “1” is ...the feature is not chosen for ...ranked, based ...
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Text Document Classification using Ant Colony Optimization and Genetic Algorithm
... of feature space which improves the efficiency and performance of ...problemof feature selection in text ...five feature selectionmeasures for text categorization, which includes ...
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The Analysis of GCFS Algorithm in Medical Data Processing and Mining
... Abstract: Feature selection plays a significant part in medical data processing and mining, it can reduce the dimensionalities of datasets and enhance the performance of the classifiers, and it is also ...
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Kernel Nearest Neigh-Bour Based Genetic Algorithm And Modified Kernel-Based Fuzzy C-Means Based MRI Image Brain Tumor Segmentation And Classification
... Hybrid Feature Extraction (HFE) performed on the segmented image to increase the feature ...The feature selection (FS) process was performed by Kernel Nearest Neighbour (KNN) based ...
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Linear Discriminant Analysis for An Efficient Diagnosis of Heart Disease via Attribute Filtering Based on Genetic Algorithm
... In feature selection, GA is used as a random selection algorithm, that exploring large search spaces [5], which is usually required in case of attribute ...original feature set contains ...
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A micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition
... other feature selection methods, evolutionary computa- tional (EC) algorithms show powerful global search capabil- ities, and have been widely accepted as efficient techniques for feature ...
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An Optimized Recursive General Regression Neural Network Oracle for the Prediction and Diagnosis of Diabetes
... applied Feature Selection via Concave (FSC), SVM, and Robust Linear Program (RLP) in which the RLP had the highest accuracy on the Pima Indian Diabetes dataset at ...a feature selection method ...
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Hybrid GA-SVM for Efficient Feature Selection in E-mail Classification
... is based on Structural Risk Minimization (SRM), a concept in which decision planes define decision ...features. Based on this fact, the authors concluded that Neural Network and SVM are not appropriate for ...
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A Feature Selection Based on Relevance and Redundancy
... Feature selection algorithms can quickly reduce the dimensions of feature vector space, simplify the calculation and reduce the training time of models by excluding the irrelevant or redundant ...of ...
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A Review on Filter Based Feature Selection
... the feature selection is an integral component for the effective use of data mining tools and techniques ...A feature refers to an aspect of the data. Feature Selection (FS) is a method ...
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Optimized feature selection for tropical wood species recognition using genetic algorithm
... Therefore, feature selection algorithm is introduced into the system to solve the above ...problems. Feature selection is a process that makes subset selection from the original ...
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Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm
... information based algorithm that analytically selects the optimal feature for ...information based feature selection algorithm can handle linearly and nonlinearly dependent data ...
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