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  1. 1

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis
  2. 2

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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    Article
  3. 3

    Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results by Ahmad Amin, Afifah Munirah, Abdullah, Adilah Syahirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

    Published 2022
    “…Logistic Regression (LR) is the most effective algorithm for forecasting student success in Year 1 with accuracy 0.88 and Decision Tree (DT) in Year 3 with accuracy 0.9. …”
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    Proceeding Paper
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    Feature selection methods application towards a new dataset based on online student activities / Muhammad Hareez Mohd Zaki ... [et al.] by Mohd Zaki, Muhammad Hareez, Abdul Aziz, Mohd Azri, Sulaiman, Suhana, Hambali, Najidah

    Published 2023
    “…This study will perform Analysis of Variance Test (ANOVA), Chisquared Test, Recursive Feature Elimination (RFE) and Extra Tree algorithm (ET) as feature selection methods to pre-process the proposed dataset that is considered raw data. …”
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    Article
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    The comparison of interactive 3D visualization between static and animated approaches for learning binary tree topic / Mohd Zulhisam Yaakub by Yaakub, Mohd Zulhisam

    Published 2016
    “…However, the research has not consistently considered instructional approaches for learning algorithm lesson, and some researches indicated that utilized methods might not be enough. …”
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    Thesis
  8. 8

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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    Thesis
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  10. 10

    Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam by Muhammad Aizat , Zainal Alam

    Published 2023
    “…This study uses 3,067 responses which are then be coupled with a machine learning methodology (ranging from Naïve Bayesian, Generalised Linear Model, Logistic Regression, Artificial Neural Network, Decision Tree, Random Forest, and Gradient Boosted Trees) via RapidMiner Studio to expand the understanding of how categories of wealth and expenditures can affect retirement behaviour, given the increasingly important role of machine learning algorithms within the context of behavioural economics where it has been demonstrated to describe patterns and relationships in behavioural data better than standard statistical analysis. …”
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    Thesis
  11. 11

    Prediction of Fetal Health Status Using Machine Learning by Naidile S, Saragodu, Shreedhara N, Hegde, Harprith, Kaur

    Published 2024
    “…We integrated a range of machine learning algorithms, including logistic regression, support vector machines, decision trees, and random forests, to train and test our model. …”
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    Article
  12. 12

    An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

    Published 2021
    “…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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    Final Year Project / Dissertation / Thesis
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    Identifying and predicting Muslim’s community funeral funding protocols by Ibrahim, Izzul Ismail, M Ashhuri, Muhammad Hassan, Hassan, Raini

    Published 2024
    “…Selected Machine Learning algorithms such as Decision Tree, Random Forest, and Naïve Bayes were used to classify the people that will go through funeral poverty based on a selected dataset and a survey conducted. …”
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    Article
  15. 15

    Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Daud, Muhamad Aliff Imran, Ahmad Puzi, Asmarani, Sidek, Shahrul Na'im, Zainuddin, Ahmad Anwar, Mohd Khairuddin, Ismail, Abd Mutalib, Mohd Azri

    Published 2024
    “…Linear Discriminant Analysis (LDA), Decision Trees (DTs), Support Vector Machine (SVM), and K-Nearest Neighbour (KNN) algorithms have been employed to achieve better accuracy in quantifying the muscle spasticity level. …”
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    Article
  16. 16

    Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

    Published 2019
    “…The algorithm performance has been evaluated using Jaccard Index, Dice Coefficient (DC) and both false positive rate (FPR) and false negative rate (FNR). …”
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    Article
  17. 17

    Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Muhamad Aliff Imran, Daud, Asmarani Ahmad Puzi, asmarani@iium.edu.my, Shahrul Na’im, Sidek, Ahmad Anwar, Zainuddin, Ismail, Mohd Khairuddin, Mohd Azri, Abd Mutalib

    Published 2024
    “…Linear Discriminant Analysis (LDA), Decision Trees (DTs), Support Vector Machine (SVM), and K-Nearest Neighbour (KNN) algorithms have been employed to achieve better accuracy in quantifying the muscle spasticity level. …”
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    Article
  18. 18

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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    Thesis
  19. 19

    Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset by Abd Rahman, M. Hafiz Fazren, Wan Salim, Wan Wardatul Amani, Abd-Wahab, Firdaus

    Published 2020
    “…This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using several well-known machine learning algorithm such as Decision Tree, Support Vector Machine and Naïve Bayers. …”
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    Article
  20. 20

    A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…The dataset is pre-processed with Pearson correlation feature selection algorithm to discover the features which influence the students� academic performance. …”
    Conference Paper