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  1. 1

    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

    Published 2017
    “…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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  2. 2

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  3. 3

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah Satari, Nur Faraidah Muhammad Di, Yong Zulina Zubairi, Abdul Ghapor Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  4. 4

    Comparative study of clustering-based outliers detection methods in circularcircular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  5. 5
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    Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

    Published 2023
    “…artificial intelligence; artificial neural network; numerical model; prediction; regression analysis; solar power; solar radiation; Malaysia; algorithm; artificial intelligence; decision tree; Malaysia; solar energy; Algorithms; Artificial Intelligence; Decision Trees; Malaysia; Neural Networks, Computer; Solar Energy…”
    Article
  7. 7

    Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

    Published 2021
    “…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. The linear based machine learning are Logistic Regression and Generalized Linear Model while the tree based are Decision Tree and Random Forest. …”
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  8. 8

    Winsorize tree algorithm for handling outliers in classification problem by Ch’ng, Chee Keong

    Published 2016
    “…This study proposes a modified classification tree algorithm called Winsorize tree based on the distribution of classes in the training dataset. …”
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    Thesis
  9. 9

    Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

    Published 2023
    “…Article; case study; genetic algorithm; mathematical computing; process optimization; sensitivity analysis; solar radiation; statistical model; statistical parameters; support vector machine; algorithm; forecasting; human; humidity; regression analysis; solar energy; sunlight; turkey (bird); wind; Algorithms; Forecasting; Humans; Humidity; Regression Analysis; Solar Energy; Sunlight; Support Vector Machine; Turkey; Wind…”
    Article
  10. 10

    Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

    Published 2011
    “…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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    Conference or Workshop Item
  11. 11

    An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.] by Rastogi, Sarthak, Shrotriya, Archit, Singh, Mitul Kumar, Potukuchi, Raghu Vamsi

    Published 2022
    “…To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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  12. 12

    Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi by Mohd Azmi, Nur Amirah

    Published 2025
    “…Comparisons among the MAE, RMSE, and R2 on a custom-based, library-based model, along with other regression models, have been drawn on a comparative basis. …”
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    Thesis
  13. 13

    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. In this paper, single classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k – Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree is experimented. …”
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    Final Year Project
  14. 14

    Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction by Jumin E., Zaini N., Ahmed A.N., Abdullah S., Ismail M., Sherif M., Sefelnasr A., El-Shafie A.

    Published 2023
    “…Different Machine Learning algorithms have been investigated, viz. Linear Regression, Neural Network and Boosted Decision Tree. …”
    Article
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    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

    Published 2021
    “…The experiment involved five (5) common algorithms: Linear Regressor, Decision Tree Regressor, Random Forest Regressor, Ridge Regressor and Lasso Regressor. …”
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    Thesis
  17. 17

    A Random Forest Regression Based Space Vector PWM Inverter Controller for the Induction Motor Drive by Hannan M.A., Ali J.A., Mohamed A., Uddin M.N.

    Published 2023
    “…Adaptive control systems; Controllers; Decision trees; Deep neural networks; Electric drives; Electric inverters; Electric motors; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Induction motors; Inference engines; Learning algorithms; Modulation; Neural networks; Regression analysis; Tracking (position); Two term control systems; Vector spaces; Vectors; Voltage control; Adaptive neuro-fuzzy inference system; Backtracking search algorithms; Different operating conditions; Proportional integral controllers; Random forests; Space Vector Modulation; Space vector pulse width modulation; Three phase induction motor; Pulse width modulation…”
    Article
  18. 18

    Predictive models for hotspots occurrence using decision tree algorithms and logistic regression. by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…Furthermore, the logistic regression model outperforms the decision tree algorithms with the accuracy of 68.63%. …”
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  19. 19

    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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  20. 20

    Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms by Nilam Nur Amir, Sjarif, Yee, Fang Lim, NurulHuda, Mohd Firdaus Azmi, Kamalia, Kamardin, Doris Wong, Hooi Ten, Hafiza, Abas, Mubarak-Ali, Al-Fahim

    Published 2018
    “…This paper presents a comparison of three different classification algorithms namely NaiveBayes (NaiveBayes classifier), Logistic Regression (Logistic classifier) and C4.5 decision tree (J48 classifier) for bankruptcy classification analysis. …”
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