Search Results - (( model evaluation bat algorithm ) OR ( label classification using algorithm ))*
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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Comparative analysis of text classification algorithms for automated labelling of quranic verses
Published 2017“…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…The purpose of this research is to apply and evaluate the performance of Bat Algorithm for classification. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…As the result, the pattern classification accuracy is also xii increase. For examples, after applying the proposed integration system, the classification accuracy of Fisher’s Iris, Wine and Bacteria18Class has been increased from 88.67% to 96.00%, from 78.33% to 83.45% and from 93.33% to 94.67% respectively as compared to only used unsupervised clustering algorithm. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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Bat algorithm for dam–reservoir operation
Published 2018“…Hence, the bat algorithm with third-order rule curve can be considered as an appropriate optimization model for reservoir operation.…”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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Multi label ranking based on positive pairwise correlations among labels
Published 2020“…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia
Published 2024“…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”
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Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie
Published 2019“…Furthermore, most classification algorithms, using either fuzzy or non-fuzzy approaches, produce results in the form of crisp or categorical classification outcomes. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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The classification of FTIR plastic bag spectra via label spreading and stacking
Published 2021“…Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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Bat algorithm and neural network for monthly streamflow prediction
Published 2023“…Therefore, this study proposed on the development of streamflow prediction model AI techniques namely Bat algorithm (BA) and backpropagation neural network (BPNN). …”
Conference Paper -
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This, however, leads to sub-optimality of prediction accuracy as the orthogonal array design lacks in offering higher-order variable interactions, in addition to its fixed and limited variable combinations to be assessed and evaluated. This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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