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  1. 1
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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  2. 2
    Phishing attack detection using machine learning method

    Phishing attack detection using machine learning method by Jupin, John Arthur

    Published 2019
    “…After a study has been made, machine learning method is used to prevent the phishing attack. …”
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    Undergraduates Project Papers
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  3. 3
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…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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  4. 4
    Impact learning : A learning method from feature’s impact and competition

    Impact learning : A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
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  5. 5
    Impact learning: A learning method from feature's impact and competition

    Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
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  6. 6
    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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  7. 7
    Impact learning: A learning method from feature’s impact and competition

    Impact learning: A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Muzahid, Abu Jafar Md, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
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  8. 8
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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  9. 9
    Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks

    Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks by Sadiq, A., Yahya, N.

    Published 2021
    “…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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  10. 10
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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  11. 11
    Fast sequential learning methods on RBF-network using decomposed training algorithms

    Fast sequential learning methods on RBF-network using decomposed training algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2004
    “…This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. …”
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  12. 12
    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method

    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2024
    “…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
    Conference Paper
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  13. 13
    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates

    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
    “…The method is compared to the existing optimization methods in machine learning, namely stochastic gradient descent method (SGD) and Adam. …”
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  14. 14
    Alternate methods for anomaly detection in high-energy physics via semi-supervised learning

    Alternate methods for anomaly detection in high-energy physics via semi-supervised learning by Md. Ali, Mohd. Adli, Badrud’din, Nu’man, Abdullah, Hafidzul, Kemi, Faiz

    Published 2020
    “…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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  15. 15
    Lexicon-based and immune system based learning methods in Twitter sentiment analysis

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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  16. 16
    A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting

    A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

    Published 2023
    Conference Paper
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  17. 17
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithms. …”
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  18. 18
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithm. …”
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  19. 19
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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  20. 20
    The forecasting of poverty using the ensemble learning classification methods

    The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

    Published 2023
    “…Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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