Search Results - (( data selection method algorithm ) OR ( pattern classification techniques algorithm ))
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1
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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2
Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…A comparison with many previous studies showed that the presented algorithm has better results outperforming those reported by earlier methods. …”
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3
First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The research on educational field that involves Data Mining techniques is rapidly increasing. Applying Data Mining techniques in an educational environment are known as Educational Data Mining that aims to discover hidden knowledge and patterns about students’ behaviour. …”
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4
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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5
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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6
The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Published 2021“…The performance of BCIs primarily depends on the efficacy of the feature extraction and feature selection techniques, as well as the classification algorithms employed. …”
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7
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
8
EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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9
EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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10
Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…At phase two, Sharp Vertex, Closed Region, and Points are added in the dataset. The top three classification algorithms were selected: IBk, LMT and Random Committee for further classification. …”
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11
Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
12
Modern fuzzy min max neural networks for pattern classification
Published 2019“…Neural network and fuzzy logic are considered to be one of the most popular soft computing techniques that applied in pattern classification domain. …”
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13
Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion
Published 2017“…The proposed algorithm takes input data from multichannel EEG timeseries, which is also known as multivariate pattern analysis. …”
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14
Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
Published 2017“…The improvement strategy calculates the energy in each channel and the selection will be based on the energy level. In order to validate the performance of the proposed technique, three motor imagery data sets are employed including RIKEN, BCI Competition III Data set IVa, and BCI Competition IV Data set I. …”
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15
Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques
Published 2024“…Manifold learning techniques aim to the non-linear dimension reduction of data. …”
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16
Systematic review for phonocardiography classification based on machine learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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17
A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…The LVQ network was observed to have poor classification for the VOCs data with classification accuracy percentage below 80%. …”
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18
Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…The improved GA is then applied for optimization and automatic design of multilayer perceptron (MLP) neural network in solving pattern classification problem. Hidden node size, initial weights and feature selection of the MLP that play significant role in the classification performance are selected to be automatically optimized by the improved GA. …”
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19
Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods
Published 2023“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods
Published 2023“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. Methods: Manual segmentation involved selecting a region-ofinterest (ROI) in images from the Bosphorus dataset to generate ground truth data. …”
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