Search Results - (( feature classification techniques algorithm ) OR ( using function methods algorithm ))
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm
Published 2021“…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…A statistical metric-based feature selection algorithm is then adopted to identify the reduced set of features to represent the original feature space. …”
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Alternative Relative Discrimination Criterion Feature Ranking Technique for Text Classification
Published 2023“…In text classification challenges, FS algorithms based on a ranking approach are employed to improve the classification performance. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The improvement process involved segmentation, feature selection and classification techniques. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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Classification of Mammogram Images Using Radial Basis Function Neural Network
Published 2020“…This paper presents the classification method for mammogram Image using Radial Basis Function Network (RBF) technique. …”
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Book Chapter -
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Hybrid binary whale with harris hawks for feature selection
Published 2022“…With the new hybrid feature selection method, the WOA algorithmâ��s efficiency was improved. …”
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah
Published 2012“…Then principal component analysis (PCA) was applied to normalize the extracted features.Novel techniques of auto-alignments with shape index procedures was developed here,where auto-alignments function was used to aligned image objects with horizontal coordinates to extracted object features in similar position. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Among all these techniques, classification is one of the most commonly used tasks in data mining, which is used by many researchers to classify instances into two or more pre-determined classes. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks
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Modern fuzzy min max neural networks for pattern classification
Published 2019“…To build an efficient classifier model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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An efficient anomaly intrusion detection method with evolutionary neural network
Published 2020“…To overcome the aforementioned issues, in this research proposed anomaly based detection is designed with Evolutionary Neural Network (ENN) by three different detection methods. The first anomaly detection method is designed using a new feature selection technique called Mutation Cuckoo Fuzzy (MCF) and evolutionary neural network classification called MultiVerse Optimizer- Artificial Neural Network (MVO-ANN) to improve the performance and execution time. …”
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Face emotion recognition using artificial intelligence techniques
Published 2008“…In the case of second classification technique, two forms of fuzzy c-mean clustering are considered and their performances are compared. …”
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An efficient computational intelligence technique for classification of protein sequences
Published 2014“…In this paper, a frequency-based feature encoding technique has been used in the proposed framework to represent amino acids of a protein's primary sequence. …”
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