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  1. 1
    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media

    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

    Published 2024
    “…However, despite the large number of studies on the analysis of mental health disorders, the predominant algorithm in the existing literature is the Multi-Class Single-Level (MCSL) classification algorithm, which is often used for simple classification tasks involving a limited number of classes. …”
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  2. 2
    Symmetric Key Size for Different Level of Information Classification

    Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

    Published 2006
    “…Therefore confidential information is normally protected by using cryptographic algorithms. In these algorithms, key is an important element since it is one of the parameters that determine the level of security that the algorithms can provide. …”
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    Conference or Workshop Item
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  3. 3
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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    Thesis
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  4. 4
    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves

    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

    Published 2023
    “…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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    Book Section
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  5. 5
    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling

    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    Conference Paper
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  6. 6
    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level

    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

    Published 2022
    “…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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    Monograph
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  7. 7
    Network game (Literati) / Chung Mei Kuen

    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…This thesis steps towards developing a networked game, Literati game system that supporting two players at one time. …”
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  8. 8
    Automatic classification of medical x-ray images

    Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

    Published 2013
    “…Experimental results showed the classification performance obtained by exploiting LBP and BoW outperformed the other algorithms with respect to the image representation techniques used.…”
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  9. 9
    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    “…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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  10. 10
    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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    Final Year Project
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  11. 11
    Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features

    Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features by Siti Fairuz, Abdullah, Ahmad Fadzli Nizam, Abdul Rahman, Zuraida, Abal Abas, Wira Hidayat, Mohd Saad

    Published 2016
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  12. 12
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Several methods have been used to classify the ASD from non-ASD people. However, there is a need to explore more algorithms that can yield better classification performance. …”
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  13. 13
    Jogging activity recognition using k-NN algorithm

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  14. 14
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…The low-level features such as edges, blobs, and ridges were extracted for grouping and classification. …”
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    Final Year Project / Dissertation / Thesis
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  15. 15
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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  16. 16
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    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 method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  17. 17
    A Real time specific weed discrimination system using multi-Level wavelet decomposition

    A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

    Published 2009
    “…The developed algorithm was used for the real time specific weed discrimination employing multi-level wavelet decomposition. …”
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    Citation Index Journal
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  18. 18
    A Real time specific weed discrimination system using multi-Level wavelet decomposition

    A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

    Published 2009
    “…The developed algorithm was used for the real time specific weed discrimination employing multi-level wavelet decomposition. …”
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    Citation Index Journal
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  19. 19
    IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH

    IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH by MOHD YAKOP, SITI HAJAR

    Published 2006
    “…The objective of this project is to develop algorithms inMATLAB and be able to implement image texture analysis by using the developed algorithms. …”
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    Final Year Project
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  20. 20
    Extremal region detection and selection with fuzzy encoding for food recognition

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…In the third algorithm, a soft assignment technique using fuzzy encoding is used to transform low-level features into a higher-level feature representation. …”
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