Search Results - (( java application optimisation algorithm ) OR ( software machine learning algorithm ))

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    Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

    Published 2022
    “…The goals of this paper are to: 1) provide fundamental experimental works of the machine learning implementation based on a new rapid software framework and 2) present the ability of machine learning in classifying students’ attitude towards video-based learning. …”
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    Article
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    Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

    Published 2017
    “…Software requirement specification (SRS) document is the most crucial document in software development process. …”
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    Thesis
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    Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

    Published 2021
    “…This paper provides an insight of a rapid software framework for implementing machine learning. …”
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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Software effort estimation using machine learning technique by Rahman, Mizanur, Roy, Partha Protim, Ali, Mohammad, Gonçalves, Teresa, Sarwar, Hasan

    Published 2023
    “…In order to better effectively evaluate predictions, this study recommends various machine learning algorithms for estimating, including k-nearest neighbor regression, support vector regression, and decision trees. …”
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    The influence of machine learning on the predictive performance of cross-project defect prediction: empirical analysis by Bala, Yahaya Zakariyau, Samat, Pathiah Abdul, Sharif, Khaironi Yatim, Manshor, Noridayu

    Published 2024
    “…This empirical investigation delves into the influence of machine learning (ML) algorithms in the realm of cross-project defect prediction, employing the AEEEEM dataset as a foundation. …”
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