Search Results - (( developing perspective classification algorithm ) OR ( java evaluation modified algorithm ))

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  1. 1

    An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

    Published 2020
    “…Deoxyribonucleic acid (DNA) microarray analysis is one of the modern cancer diagnosis techniques used by scientists to measure the gene expression level changes in gene expression data. From the perspective of computing, an algorithm is developed to ease the diagnosis process, but the feasibility is not reliable. …”
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  2. 2

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. …”
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  3. 3

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  4. 4

    Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

    Published 2024
    “…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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  5. 5

    Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions by Adday, Ghaihab Hassan, K. Subramaniam, Shamala, Ahmad Zukarnain, Zuriati, Samian, Normalia

    Published 2022
    “…This survey provides an elaborate classification and analysis of fault tolerance structures and their essential components and categorizes errors from several perspectives. …”
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  6. 6

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…In order to perform early human action detection, the conventional classification problem is modified into frame-by-frame level classification. …”
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  10. 10

    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

    Published 2015
    “…There are three categories of evaluation of RS predictive accuracy metrics, classification accuracy metrics and rank accuracy metrics. …”
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  11. 11

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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  12. 12

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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  13. 13

    Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks by Nirabi, Ali, Abd Rahman, Faridah, Habaebi, Mohamed Hadi, Sidek, Khairul Azami, Yusoff, Siti Hajar

    Published 2025
    “…By providing a solid foundation for the development of algorithms capable of detecting and classifying stress levels, the dataset supports innovations in non-invasive monitoring tools and contributes to personalized healthcare solutions that can adapt to the cognitive states of users. …”
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