Search Results - (( perspective classification using algorithm ) OR ( java implementation bayes algorithm ))

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  1. 1

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…In this system, the layout was designed under two categories which are the standard bay size and the small bay size to increase the parking bays. …”
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  2. 2

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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  3. 3

    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan by Nik Mazlan, Nik Aidil Syawalni

    Published 2024
    “…The motifs and textures each convey distinct philosophical perspectives on life. The classification of certain patterns may vary due to differences in the perspectives of individual classifiers, leading to potential inconsistencies. …”
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  4. 4

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…Recently, the swarm-based hybrid algorithms have given significant performance in cancer classification. …”
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  5. 5

    The Perspective Classification of Balanced Scorecard with Ontology Technique by Kaewninprasert, Kittisak, Chai-Arayalert, Supaporn, Yamaqupta, Narueban

    Published 2024
    “…This paper aims to present the Perspective Classification of Balanced Scorecard with Ontology (PCBSC-Onto) framework for automatically classifying performance indicators into BSC’s four perspectives using an ontological approach to support the dynamic capability of the management system’s performance. …”
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  6. 6

    Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

    Published 2013
    “…Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. …”
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  7. 7

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  8. 8

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  9. 9

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

    Published 2020
    “…From the perspective of computing, an algorithm is developed to ease the diagnosis process, but the feasibility is not reliable. …”
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  10. 10

    Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

    Published 2023
    “…Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. …”
    Article
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    Iban Plaited Mat Motif Classification using Adaptive Smoothing by Silvia, Joseph

    Published 2024
    “…To address this issue, an improved classification method with adaptive smoothing is proposed. …”
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  13. 13

    Comparison between fuzzy and non-fuzzy classification methods in the prediction of residential household water leakage / Nor Aishah Md Noh, Dr. Khairul Anwar Rasmani and Nur Rasyid... by Md Noh, Nor Aishah, Rasmani, Khairul Anwar, Mohd Rashid, Nur Rasyida

    Published 2013
    “…Therefore this research looks into the potential use of fuzzy rule-based approaches from a new perspective where mathematical models generated using data related to water collected from the consumer consumption. …”
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  14. 14

    Implementation of lightweight cryptographic primitives by Hammad B.T., Jamil N., Rusli M.E., Z�Aba M.R., Ahmed I.T.

    Published 2023
    “…These classifications are very useful because the primitives have different and sometimes contrary characteristics. …”
    Article
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    Implementation of lightweight cryptographic primitives by Hammad B.T., Jamil N., Rusli M.E., Z�Aba M.R., Ahmed I.T.

    Published 2023
    “…These classifications are very useful because the primitives have different and sometimes contrary characteristics. …”
    Article
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    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 current study contributes to the literature by highlighting decision tree and rule-based classification models as very useful in the Malaysian e-commerce context. …”
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    Advances in automatic insect classification by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…We provides discussion on the state-of-the-art and provides perspective on future research direction in insect recognition and classification problem.…”
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    Vision based entomology: a survey by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…We provides discussion on the state-of-the-art and provides perspective on future research direction in insect recognition and classification problem.…”
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