Feature selection methods
A kernel-based multivariate feature selection method for microarray data classification.
... multivariate-based feature filter method for cancer classification, namely, kernelPLS- based filter ...in feature selection techniques to improve classification ...our feature selector with ...
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AN ANN APPROACH FOR NETWORK INTRUSION DETECTION USING ENTROPY BASED FEATURE SELECTION
... classification methods, namely, Radial Basis Function Network, Self- Organizing Map, Sequential Minimal Optimization, and Projective Adaptive Resonance Theory have been ...based feature selection ...
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Providing a Security Model Based on Service Oriented Architecture in Electronic Banking
... on feature selection has been ...and feature selection methods are examined and the best design is selected and it is compared with another similar works by considering different ...
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Information Gain Feature Selection for Multi-Label Classification
... many feature selection methods have been developed to allow the identification of relevant and informative features for multi-label ...most methods proposed for this task rely on the ...
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A decision-tree-based model for evaluating the thermal comfort of horses
... The feature selection methods used to reduce computational cost and simplify predictive learning decreased model accuracy to 70 %; however, the model became simpler with easily interpretable ...these ...
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Unbalance Quantitative Structure Activity Relationship Problem Reduction in Drug Design
... Different methods have been applied to QSAR problems [17,23,24] and shown that proper feature selection of molecular descriptor will help improve the prediction ...the feature selection ...
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Document features selection using background knowledge and word clustering technique
... of feature space is very high, which increases the cost and reduces the performance of classification algorithms (Sebastiani, 2002; Shang et ...some methods to reduce the data size and to increase the ...
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Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
... different methods was not ...three methods and seven with only one of the two other methods; five features were specific for the CFS-FS ...different methods may select different features ...
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Morphological feature selection and neural classification
... full feature vector to act as a benchmark. Two feature vector optimisation methods were examined, correlation analysis and ...both feature selection methods matched the ...
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Maximal Information Coefficient and Support Vector Regression Based Nonlinear Feature Selection and QSAR Modeling on Toxicity of Alcohol Compounds to Tadpoles of Rana temporaria
... nonlinear feature selection methods involved in MIC and SVR can effectively eliminate irrelevant ...The methods proposed in this study have a potential application in the QSAR research field ...
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Higher order feature extraction and selection for robust human gesture recognition using CSI of COTS Wi-Fi devices
... cumulant feature extraction to maximize the recognition ...of feature inputs. Hence the present approach implements optimal feature selection methods that enable the machine learning ...
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Semi-supervised feature selection
... unsupervised feature selection ...These methods have some interesting advantages and among then we can highlight that they are unbiased by any experimental expert, they perform well in the absence of ...
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Building Customers` Credit Scoring Models with Combination of Feature Selection and Decision Tree Algorithms
... features selection algorithms, are less than models built with all the features of ...with feature selection methods are more accurate than models with all ...
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Feature selection for neuroimaging applied to word-category identification in dyslexic children
... univariate methods, such as correlation analysis and ICA that we have seen in Section ...univariate methods, the authors propose to analyse rsFC with multivoxel pattern analysis ...univariate ...
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Multiobjective optimization of classifiers by means of 3-D convex Hull based evolutionary algorithms
... a selection scheme which is used to choose winner individuals to survive from populations at the same ...contribution selection scheme is adopted to calculate the contribution to the volume of 3-D ROCCH of ...
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Sparse Spatial Coding: a novel approach for efficient and accurate object recognition
... Recognizing objects in images has been a challenging task, and for a good number of years it has attracted the attention of a large number of researchers from sev- eral research communities such as robotics, computer ...
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Multi Object Tracking Using Feature Selection Based Particle Swarm Optimization
... The computer vision and image processing can be a tool for video surveillance system. Control the traffic consists two step: motion detection and object tracking. For tracking the vehicles trajectories should be ...
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Image Mining for Mammogram Classification by Association Rule Using Statistical and GLCM features
... of feature selection is proposed which approximately reduces 60% of the features and association rule using image content is used for ...for feature selection provides the best optimal ...
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Markov Blanket based Feature Selection: A Review of Past Decade
... each feature subset, and the outcome is tailored to a particular ...as feature ranking since they imply that irrelevant features are useless though it is proved not true [2], ...Embedded methods ...
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MATERIALS AND METHODS Selection of milk producing farms
... Considering the importance of these small milk producers to the market and the well-known health risks associated to consumption of raw milk, this study evaluated the microbiological qua[r] ...
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