Search Results - (( based optimization based algorithm ) OR ( pattern classification problem algorithm ))

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    A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

    Published 2010
    “…There is a training set for each class. Those problems occur in a wide range of human activity. One of the most promising ways to data classification is based on methods of mathematical optimization. …”
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    Article
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    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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    Thesis
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    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    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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    Thesis
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    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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    Thesis
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    Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

    Published 2014
    “…Deriving useful and interesting rules from a data mining system is an essential and important task. Problems such as the discovery of random and coincidental patterns or patterns with no significant values, and the generation of a large volume of rules from a database commonly occur. …”
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    Article
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    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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    Thesis
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    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

    Published 2024
    “…The class imbalance makes estimating building damage grades difficult, emphasizing the necessity for careful modeling. Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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    Article
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    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…This paper proposes a competitive grey wolf optimizer (CGWO) to solve the feature selection problem in electromyography (EMG) pattern recognition. …”
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    Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

    Published 2016
    “…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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    A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

    Published 2023
    “…This paper presents a genetic-algorithm-based fuzzy inference system for extracting highly comprehensible fuzzy rules to be implemented in human practices without detailed computation (hereafter denoted as GA-FIS). …”
    Article
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    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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    Thesis
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    A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

    Published 2023
    “…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
    Article
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    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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    Thesis
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    Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

    Published 2007
    “…A package of software based on neuro fuzzy model (ANFIS) has been developed using MATLAB software and optimization were done with the help from WEKA. …”
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    Book Section
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    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…One of the most popular BCI type is Electroencephalography (EEG)-based BCI, where motor imagery is considered one of the most effective ways. …”
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    Article
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    Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

    Published 2023
    “…The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.…”
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    Conference or Workshop Item
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