Search Results - (( data selection method algorithm ) OR ( parameter implementation learning algorithm ))

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  1. 1

    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 research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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    Article
  2. 2

    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

    Published 2022
    “…Yet, the LDA cannot be implemented directly on unsupervised data as it requires the presence of class labels to train the algorithm. …”
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    Book Chapter
  3. 3

    Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques by Anifowose, Fatai Adesina

    Published 2015
    “…In this thesis, new non-linear feature-selection assisted methods and ensemble learning models are proposed. …”
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    Thesis
  4. 4

    A Mininet emulation study for SDN fat tree data center sleep mode routing algorithms by Fawzi S., Din N.M.

    Published 2025
    “…Employing sleep mode aligns with sustainability goals and can reduce the environmental impact of data centers by lowering carbon emissions. In this work meta heuristic algorithm is incorporated at the SDN central controller in a fat tree-based data centre for bandwidth usage monitoring, sleep decisions and path selection using Mininet emulation. …”
    Article
  5. 5

    Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs by Liew, W.S., Seera, M., Loo, C.K., Lim, E.

    Published 2015
    “…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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    Article
  6. 6

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…Classification performance can be improved by implementing a reliability threshold for training data. …”
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    Conference or Workshop Item
  7. 7

    An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

    Published 2020
    “…Despite this ease, the selection of ESN parameters and topology is a considerable design challenge. …”
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    Article
  8. 8

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…A lot of researches have been done to predict the reservoir parameters using well log data through applying various methods. …”
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    Thesis
  9. 9

    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
    Article
  10. 10

    Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach by Hamid, Norfarhanah

    Published 2021
    “…Based on the feature selection, model development was built with and without input selection using the Nonlinear Autoregressive with Exogeneous Input (NARX) neural network model which made use of 10 number of hidden neurons and 2 number of delays, implementing Levenberg-Marquardt as training algorithm. …”
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    Monograph
  11. 11

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

    Published 2025
    “…Traditional methods struggle to model these complexities effectively, necessitating adoption of advanced algorithms to improve accuracy. …”
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    Thesis
  12. 12

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…Deep Neural Network (DNN) is a combination method between two different subfields of Machine Learning application, including the Artificial Neural Network (ANN) and Deep Learning (DL). …”
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    Thesis
  13. 13

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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    Thesis
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    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

    Published 2016
    “…The correlation-based feature selection (CFS) method was used to select representative WPD vector subset to eliminate redundancy before combining with other features. …”
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    Thesis
  16. 16

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…In our method, we select data that are located in untrained or “not well-learned” region and discard data at trained or “well-learned” region. …”
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    Thesis
  17. 17

    Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

    Published 2024
    “…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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    Thesis
  18. 18

    Multi-hop and mesh for LoRa networks: Recent advancements, issues, and recommended applications by Andrew Wei-loong Wong, Say leng goh, Mohammad Kamrul Hasan, Salmah Fattah

    Published 2024
    “…The upcoming trend of implementing machine learning algorithms to multi-hop and mesh LoRa networks opens up a wide range of possibilities, ranging from airspace efficiency, efficient route selection, and improving data throughput. …”
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    Article
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