Search Results - regression ((((((new algorithm) OR (_ algorithm))) OR (tree algorithm))) OR (based algorithm))

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  1. 1

    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
  2. 2

    Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

    Published 2013
    “…Therefore spatial objects should be included in forest fires datasets for classifying hotspots occurrence in order to obtain the classifiers with high accuracy. This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
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  3. 3

    Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

    Published 2019
    “…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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  4. 4

    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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    Article
  5. 5

    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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  6. 6

    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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  7. 7

    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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  8. 8

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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  9. 9

    Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

    Published 2024
    “…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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    Article
  10. 10

    Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

    Published 2021
    “…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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  11. 11
  12. 12

    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

    Published 2024
    “…Thirdly, this study uses SHAP framework to improve the interpretability of the new algorithm (EBGWO-CatBoost), and solves the problem of the weak interpretability of the new algorithm. …”
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  13. 13

    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
  14. 14

    A review of deep learning and machine learning techniques for hydrological inflow forecasting by Latif S.D., Ahmed A.N.

    Published 2024
    “…In this study, we look at the long short-term memory deep learning method as well as three traditional machine learning algorithms: support vector machine, random forest, and boosted regression tree. …”
    Review
  15. 15

    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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  16. 16

    A New Optimization Algorithm based on Copulation Behavior of Simine Jackals by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

    Published 2011
    “…This work introduces a new meta-heuristic algorithm, termed as Simine Jackal algorithm, designed to solve optimization problems. …”
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  17. 17

    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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  18. 18

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    Published 2024
    “…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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  19. 19

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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  20. 20

    Improved nu-support vector regression algorithm based on principal component analysis by Abdullah Mohammed, Rashid, Habshah, Midi

    Published 2023
    “…This paper focuses on improving the nu-SVR algorithm to handle the problem of outliers. A new hybrid PCA with the nu-SVR technique (PCA-SVR) has been established. …”
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