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  1. 1
    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…In conclusion, it can be inferred from the analysis that the Random Forest model has better predictive performance compared to the rest of the pallet level partition model with a height of 12 cm used in this research. …”
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    Thesis
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  2. 2
    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak

    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

    Published 2022
    “…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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    Monograph
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  3. 3
    Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba

    Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba by Ghulam , Mujtaba

    Published 2018
    “…These master feature vectors were fed as input to six machine learning algorithms to construct and evaluate the classification models. …”
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  4. 4
    Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring

    Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring by Abualsaud, Khalid, Mahmuddin, Massudi, Hussein, Ramy, Mohamed, Amr

    Published 2013
    “…A reconstructed algorithm derived from DCT of daubechie’s wavelet 6 is used to decompose the EEG signal at different levels. …”
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    Conference or Workshop Item
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  5. 5
    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
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  6. 6
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…The classification accuracy of the RF classifier is observed to be higher than that of SVM using either all features or only the optimal features. …”
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  7. 7
    Classification and visualization of e-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi

    Classification and visualization of e-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi by Ahmad Kushairi, Nuwairah Aimi

    Published 2023
    “…It means a significant difference exists between the time taken for manual evaluation and the evaluation using the web-based system. …”
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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform

    A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform by Mahmmod, Basheera M.

    Published 2018
    “…As a conclusion, the proposed SEA enhances and improves noisy signals and regain clean signals with less RN and SD, reducing MN level. Moreover, best improvement in quality and intelligibility properties is obtained particularly in high noise levels.…”
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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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