radial basis function classifier
ON MODELING TRACES IN A COMPUTING ENVIRONMENT FOR HUMAN LEARNING BASED INDICATORS
... Bagging classifier produces a meta-model using a machine learning classifier, k nearest neighbour classifier produces a stagnant model, Radial Basis Function Network ...
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EEG-based Mind Driven Type Writer by Fuzzy Radial Basis Function Neural Classifier
... The second model also includes three layers, where the first layer comprises interval type-2 fuzzy MFs (IT2FMFs) [18]. The second and the third layer are similar with that of Model I. The IT2FMFs layer in Model 2 helps ...
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An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks
... the classifier performance could be affected by data pre- processing; especially, it could depend on whether data are normalized or ...error basis when a learning algorithm is applied to a par- ticular ...
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Face Recognition by Radial Basis Function Network (RBFN)
... In this paper, an effective method of face recognition technique has been presented. Image processing algorithms based on Radial basis function network has been used in this paper. This paper ...
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Differentiation of Soft Bone Strength in Human Femur Radiographic Images Using Sharpness Features and Extreme Learning Machine
... E-ELM classifier using radial basis activation function performs better in terms of classification accuracy (99%) for the features selected using ICA ...
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Using SVM as Back-End Classifier for Language Identification
... Robust automatic language identification (LID) is a task of identifying the language from a short utterance spoken by an unknown speaker. One of the mainstream approaches named parallel phone recognition language ...
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A radial basis classifier for the automatic detection of aspiration in children with dysphagia
... Examining the value of dispersion ratios in Figure 5, we note that aspirations tend to have dispersion ratios less than one. Bearing in mind the influence functions [55] for mean absolute deviation and interquartile ...
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Face Recognition using Rectangular Feature
... height and width are considering for calculation the pixel values on particular point in an image. We have to calculate face feature vector using principal component analysis (PCA). We have taken three features eyes, ...
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Unified Noise Reduction using Adaptive Radial Basis Function
... method of removing the speckle noise from SAR images with better performance by modifying the window size of Lee filter and then compressing by using wavelet transform. [15] Proposed an algorithm to restore noisy images ...
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Performance Analysis of Automobile data using Bagged Ensemble Classifiers
... bagging classifier in conjunction with radial basis function and support vector machine as the base learner and the performance comparison has been demonstrated using Auto Imports and Car ...
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Earlier Detection of Glaucoma using Empirical Wavelet Transform
... The ranked features are classified using the Least Squares Support Vector Machine (LS-SVM) classifier with kernels such as Radial Basis Function (RBF), Morlet wavelet and Mexican-hat wavelet. ...
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Classifying ReachOut posts with a radial basis function SVM
... second classifier would have been chosen, but using Dev_test2 we would have chosen the ...second classifier hap- pened to correctly classify one of the 8 examples for crisis in Dev_test1, but missed all the ...
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Approximation of function and its derivatives using radial basis function networks
... of radial basis function based on a set of 250 test ...approximate function obtained from all networks are quite low and hence the global shape of the orig- inal function is well ...
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C2-Element radial basis function methods for some continuum mechanics problems
... where h is the mesh size. Direct methods clearly cannot converge when h > ǫ and it thus requires a mesh size to be much smaller than the small length scale (h ≪ ǫ). It can be seen that tremendous amounts of computer ...
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Learning Methods of Radial Basis Function Neural Network
... Radial Basis Function Neural Network （ RBF ） is widely used now; it can solve the following problems: the small sample, nonlinear, dimension and local ...
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Deep graph regularized learning for binary classification
... of classifier learning with small labeled data, we propose a novel neural network based on iterative quadratic programming (QP) with graph Lapla- cian regularizer (GLR), combining the merits of model-based and ...
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Preconditioning for radial basis function partition of unity methods
... Meshfree radial basis function (RBF) methods are of interest for solving par- tial differential equations due to attractive convergence properties, flexibility with respect to geometry, and ease of ...
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Writer Identification and Recognition Using Radial Basis Function
... the basis of scanned images of handwriting is a useful biometric modality with application in forensic and historic document analysis and constitutes an exemplary study area within the research field of behavioral ...
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Benchmarking of the Key Sample Machine
... When use Gaussian function as indicator functions in LS approximation, it looks a bit like the RBFN. Actually it can be looked as a special case of RBFN when Gaussian functions are use in the hidden layer with ...
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Compact integrated radial basis function modelling of particulate suspensions
... integrated radial basis functions (CIRBF), for the simu- lation of heat transfer and steady/unsteady viscous flows in complex geometries, and their applications for the prediction of macroscopic rheological ...
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