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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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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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Evaluation of fall detection classification approaches
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WCBP: A new water cycle based back propagation algorithm for data classification
Published 2016“…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…According to previous works, conventional FS methods not only minimize the number of features but also enhance the classification performance. …”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…We use two common benchmark classification problems to illustrate the improvement in convergence time.…”
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
Published 2022“…To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle
“…As the results, the accuracy of CNN classification has improved at least 6 percent compared to the conventional algorithms.…”
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Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network
Published 2021“…However, conventional bottom-up saliency map algorithms regularly failed to localize salient or pathological anomalies in medical images. …”
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Next generation insect taxonomic classification by comparing different deep learning algorithms
Published 2022“…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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Image Classification On Ex-Mining Land Area Using Echo Classifier
Published 2003“…Study goals included evaluation of various classification algorithms, deriving a landcover map of the ex-mining land using satellite image and collection of ground truth points in order to perform a more quantitative analysis and accuracy assessment of the methods used.…”
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Passive forward scatter radar based on LTE signal for vehicle detection and classification
Published 2018“…The Doppler spectrum scattered by the vehicle is used as the features for input to the classification system. …”
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Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…The MLP networks are trained using two types of learning algorithm, which are the Levenberg Marquardt and the Resilient Back Propagation algorithms. …”
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Hybrid signal processing and machine learning algorithm for adaptive fault classification of wind farm integrated transmision line protection
Published 2019“…The supervised machine learning algorithm from Bayesian network classified 99.15 % faults correctly with the operation time of 0.01 s to produced best-generalized model with an RMS error value of 0.05 for single line-to-ground (SLG) fault identification and classification. …”
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Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks
Published 2025“…Despite the growing use of MHAs, existing studies often focus on specific subsets of algorithms or narrow application domains, leaving a gap in understanding their comprehensive potential and comparative performance across diverse classification tasks. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. …”
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