Search Results - (( using reduction methods algorithm ) OR ( parameter classifications using algorithm ))

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  1. 1

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…Two data reduction methods were used 1) feature selections methods and 2) principal component analysis (PCA). …”
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    Thesis
  2. 2

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  3. 3

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  4. 4

    Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

    Published 2021
    “…If we use the appropriate features, then the k-NN will be a reliable algorithm. …”
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    Article
  5. 5

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…This proposed classifier achieved 97.9% classification accuracy on the ISIC dataset. In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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    Thesis
  6. 6

    Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

    Published 2011
    “…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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    Thesis
  7. 7

    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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    Article
  8. 8

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

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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    Thesis
  9. 9
  10. 10

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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    Thesis
  11. 11

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. The objective of this study is to develop an accurate and efficient model capable of recognizing the presence of children in cars based on sound data. …”
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    Student Project
  12. 12

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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    Thesis
  13. 13

    Non-fiducial based ECG biometric authentication using one-class support vector machine by Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad

    Published 2017
    “…Moreover, one-class SVM can be robust recognition algorithm for ECG biometric verification if the sufficient number of biometric samples is available.…”
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    Conference or Workshop Item
  14. 14

    An enhanced gated recurrent unit with auto-encoder for solving text classification problems by Zulqarnain, Muhammad

    Published 2020
    “…However, GRU suffered from three major issues when it is applied for solving the text classification problems. The first drawback is the failure in data dimensionality reduction, which leads to low quality solution for the classification problems. …”
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    Thesis
  15. 15

    Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

    Published 2012
    “…Therefore, a new classification proposed on the natural gas networks from the oil and gas wells to the consumers. …”
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    Thesis
  16. 16

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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    Thesis
  17. 17

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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    Article
  18. 18

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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    Article
  19. 19

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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    Thesis
  20. 20

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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    Conference or Workshop Item