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1
Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. …”
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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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3
Training functional link neural network with ant lion optimizer
Published 2020“…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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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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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
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7
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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8
Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification
Published 2024“…The proposed algorithm, named the CFS-Mutable Composite Firefly Algorithm (CFS-MCFA), is evaluated based on two metrics, namely classification accuracy and genes subset size, using a Support Vector Machine (SVM) classifier. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…Firstly, a non-linear time-varying modified Sigmoid transfer function is used as the binarization method. Second, a hybrid Logistic-Tent chaotic map is employed to substitute the pseudorandom numbers of the probability operator in standard WOA. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…It shows that the IQR-HEOM method is more efficient to rectify the problem caused by using range in HEOM. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…This method does not explicitly use derivatives, and is particularly appropriate when functions are non-smooth. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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An ensemble method with cost function on churn prediction
Published 2019“…In telecommunication businesses, companies have used various types of single classifiers to classify customer churn, but the classification accuracy is still relatively low. …”
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Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification
Published 2024“…Deep learning has recently dramatically improved the cutting edge in a wide range of artificial intelligence jobs. Hence, this study proposed hybrid deep learning algorithms for ASD classification. …”
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Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
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