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  1. 1

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…However, these semi-supervised multi-task selection feature algorithms are unable to naturally handle the multi-view data since they are designed to deal with single-view data. …”
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    Thesis
  2. 2

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

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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    Thesis
  3. 3

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. …”
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    Article
  4. 4

    Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms by Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.

    Published 2023
    “…Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms…”
    Conference Paper
  5. 5

    Performance comparison of feature selection methods for prediction in medical data by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Amir Hussin, Amir 'Aatieff

    Published 2023
    “…This study analyzes filter, wrapper, and embedded feature selection methods for medical data with the predictive machine learn- ing algorithm, Random Forest and CatBoost. …”
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    Proceeding Paper
  6. 6

    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…We enhanced the Q-Learning algorithm for action selection based on potential action abilities and proposed a tool, namely CrashDroid, that allows the automation of testing context-aware Android applications. …”
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    Thesis
  7. 7

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
  8. 8

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…The deliverable of this phase is the selection of the best candidate of machine learning algorithm for university campus energy load prediction. …”
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    Thesis
  9. 9

    Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim by Halim, Zulkifli

    Published 2023
    “…Hence, the question arises about selecting the optimal model: the characteristic data for CCRA and the best practice machine learning pipelines. …”
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    Thesis
  10. 10

    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
    “…Besides, these algorithms have adopted manifold learning to leverage both the unlabeled and labeled data since its laborious to obtain adequate labeled training data. …”
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    Article
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    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

    Published 2024
    “…Previous studies usually concentrate on the forecasting stock index or selecting a few stocks with restricted features. Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”
    thesis::master thesis
  13. 13

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

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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    Thesis
  14. 14

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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    Thesis
  15. 15

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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    Article
  16. 16

    A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. By initializing data pre-processing for clean-up, noise removal, and unpredictable unfinished data, reducing the number of features in the tweet dataset using mutual information is the study's methods. …”
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    Article
  17. 17

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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    Article
  18. 18

    Dimensionality reduction in data summarization approach to learning relational data by Kheau, Chung Seng, Rayner Alfred, Lau, Hui Keng

    Published 2013
    “…Based on the experimental results, the DARA algorithm is proven to be very effective in learning relational data. …”
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    Book
  19. 19

    Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

    Published 2020
    “…In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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    Article
  20. 20

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

    Published 2016
    “…Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
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    Conference or Workshop Item