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On classification problem of Loday algebras
Published 2016“…This is a survey paper on classification problems of some classes of algebras introduced by Loday around 1990s. …”
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Predicting protein-protein interactions as a one-class classification problem
Published 2006“…Therefore, in this paper we solve this problem as a one-class classification problem using One-Class SVM (OCSVM). Using only positive examples (interacting protein pairs) for training, the OCSVM achieves accuracy of 80%. …”
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Solving classification problem using ensemble binarization classifier
Published 2018“…One-Versus-All (OVA) is one of the strategies which transforming the ordinal multi-class classification problems into a series of two-class classification problems. …”
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An experimental study of the extended NRBF regression model and its enhancement for classification problem
Published 2008“…Moreover, since the ENRBF model is initially proposed for the regression and function approximation problems, a further step is taken in this work to modify the ENRBF model to deal with the classification problems. Both the original ENRBF model and the new proposed ENRBF classifier (ENRBFC) can be viewed as the special cases of the mixture-of-experts (ME) model that is discussed in Xuetal. …”
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A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification
Published 2006“…ECT measured the different capacitance value of fluid and produced the data for the classification problem. Multilayed Perceptron (MLP), a type of artificial neural network (ANN) which is widely used in a classification problem is developed using MATLAB 7®. …”
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A direct ensemble classifier for learning imbalanced multiclass data
Published 2013“…In addition, the selected benchmark data, experiments and the results are useful for future research on the imbalanced multiclass classification problem. Furthermore, the DECIML framework was applied to the real world leaf classification problem based on the shape features. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…However, GRU suffered from three major issues when it is applied for solving the text classification problems. The first drawback is the failure in data dimensionality reduction, which leads to low quality solution for the classification problems. …”
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Auto-encoder variants for solving handwritten digits classification problem
Published 2020“…All the variants of the standard AE are evaluated on the basis of the MNIST benchmark handwritten digit dataset for classification problem. The observed output reveals the benefit of using the AE model and its variants. …”
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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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A derivative-free optimization method for solving classification problem
Published 2010“…The results of numerical experiments allowed us to say the proposed algorithms are effective for solving classification problems at least for databases considered in this study.…”
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A deep learning based neuro-fuzzy approach for solving classification problems
Published 2020“…Therefore, this study also proposed a Deep Neuro-Fuzzy Classifier (DNFC) with a cooperative based structure for solving classification problems, particularly. The performance of the proposed DNFC was evaluated with ANFIS and DNN classifier, where overall results show that the performance of ANFIS classifier decreased when input size increased. …”
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