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  1. 1

    Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

    Published 2021
    “…This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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    Proceeding Paper
  2. 2

    Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

    Published 2022
    “…This paper analyzed several visual analytics approaches instantiated in machine learning algorithm for medical record analytics. …”
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    Proceeding Paper
  3. 3

    Car dealership web application by Yap, Jheng Khin

    Published 2022
    “…On the other hand, the data scientists could monitor and debug the models using a SHAP monitoring function, which was improved by the author, with the aid of effective visualizations like model loss bar plot. …”
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    Final Year Project / Dissertation / Thesis
  4. 4

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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    Thesis
  5. 5

    Stock price monitoring system by Ng, Chun Ming

    Published 2024
    “…As stock price is time series data, a time series prediction algorithm is being utilized to build a deep learning model, namely Long Short-Term Memory (LSTM). …”
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    Final Year Project / Dissertation / Thesis
  6. 6

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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    Thesis
  7. 7
  8. 8

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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    Article
  9. 9

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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    Article
  10. 10

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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    Article
  11. 11

    Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin by Nordin, Daarin Nadia

    Published 2020
    “…Thus, this project proposes a solution to the problems by utilizing the machine learning approach which is the Agglomerative clustering algorithm. …”
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    Thesis
  12. 12

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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    Monograph
  13. 13

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

    Published 2020
    “…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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    Thesis
  14. 14

    Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning by Hiu, Theresa Wei Xin

    Published 2022
    “…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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    Final Year Project / Dissertation / Thesis
  15. 15

    Unsupervised monocular depth estimation with multi-scale structural similarity powered loss function / Ali Kohan by Ali, Kohan

    Published 2020
    “…Nowadays specific hardware such as sensors, radars and multiple-view-recording cameras are being used in order to acquire depth data of a scene. Modern approaches use deep learning to address this task by trying to learn depth information in a supervised manner. …”
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    Thesis
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    Analyzing UiTMCTKKT vehicle utilization and travel pattern using predictive analytics by Syed Mohamad, Sharifah Masyitah

    Published 2025
    “…The CRISP-DM framework was adopted as the methodology to guide data preparation, modeling, and evaluation. Two key experiments were conducted using machine learning models. …”
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    Student Project
  18. 18

    Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias by Alias, Annasuha Atie Atirah

    Published 2023
    “…The goal is to empower suicide prevention organizations and concerned individuals with an efficient and accessible means of taking timely actions toward individuals at risk. The result of the data analysis is visualized into a web application system to enable the analysis results to be interpretable and readable by the user using Plotly visualization tool. …”
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    Thesis
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  20. 20

    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

    Published 2016
    “…The IncFRNN algorithm is able to control the size of training pool using predefined window size threshold. …”
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    Thesis