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  1. 1
    Formulating new enhanced pattern classification algorithms based on ACO-SVM

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  2. 2
    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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  3. 3
    Intelligent classification algorithms in enhancing the performance of support vector machine

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

    Published 2019
    “…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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  4. 4
    Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm

    Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm by Liu, Jingrui, Pan, Dongyang

    Published 2019
    “…A fully symmetric classification of the boundary value problem for a class of fractional differential equations with variable sequences is determined by using a fully symmetric differential sequence sorting algorithm. …”
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  5. 5
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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    Thesis
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  6. 6
    Using fuzzy association rule mining in cancer classification

    Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2011
    “…A wide variety of cancer datasets have been implemented by the various methods of gene selection and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. …”
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  7. 7
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…All algorithms showed more stability and accuracy when training size applied is more than 6% by the Equal Sample Rate (ESR) method with six variables. …”
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  8. 8
    Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms

    Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms by Kamarul Ismail, Nasir Nayan, Siti Naielah Ibrahim

    Published 2016
    “…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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  9. 9
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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  10. 10
    Extremal region detection and selection with fuzzy encoding for food recognition

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…The experimental results demonstrate the superior classification performance of the proposed methods over the previous methods. …”
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  11. 11
    Classification Of Cervical Cancer Stage From Pap Smear Tests

    Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

    Published 2019
    “…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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    Final Year Project
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  12. 12
    A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island

    A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

    Published 2009
    “…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. …”
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  13. 13
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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  14. 14
    A new descriptor for smile classification based on cascade classifier in unconstrained scenarios

    A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

    Published 2021
    “…We suggest a histogram-based cascade smile classification method utilizing different facial features. …”
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  15. 15
    Gene Selection For Cancer Classification Based On Xgboost Classifier

    Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

    Published 2022
    “…Due to this situation, development of the gene selection method has become more important in obtain useful information for cancer classification, and diagnoses for other diseases. …”
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    Undergraduates Project Papers
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  16. 16
    Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling

    Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling by N.S. Suhaimi, J. Teo, J. Mountstephens

    Published 2018
    “…Secondly, the data will then be tested and trained with KNN and SVM algorithms. We conduct subject-dependent as well as subject-independent classifications in order to compare intra-against inter-subject variability, respectively in VR EEG-based emotion modeling. …”
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  17. 17
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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    Monograph
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  18. 18
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

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

    Published 2012
    “…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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  19. 19
    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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  20. 20
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
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