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  1. 1
    A survey of fuzzy min max neural networks for pattern classification: variants and applications

    A survey of fuzzy min max neural networks for pattern classification: variants and applications by Al Sayaydeh, Osama Nayel, Mohammed, Mohammed Falah, Lim, Chee Peng

    Published 2018
    “…This division facilitates understanding of the improvements on the original FMM model, as well as enables identification of the limitations that still exist in various FMM-based models. We also summarize the use of FMM and its variants in solving different benchmark and real-world pattern classification problems. …”
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  2. 2
    Multilevel learning in Kohonen SOM network for classification problems

    Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

    Published 2006
    “…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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  3. 3
    An enhanced generalized adaptive resonance theory neural network and its application to medical pattern classification

    An enhanced generalized adaptive resonance theory neural network and its application to medical pattern classification by Yap K.S., Lim C.P., Mohamad-Saleh J.

    Published 2023
    “…The applicability of EGART to pattern classification and fuzzy rule extraction problems is evaluated using three benchmark medical data sets and one real medical diagnosis problem. …”
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  4. 4
    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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  5. 5
    Text classification using modified multi class association rule

    Text classification using modified multi class association rule by Kamaruddin, Siti Sakira, Yusof, Yuhanis, Husni, Husniza, Al Refai, Mohammad Hayel

    Published 2016
    “…This paper presents text classification using a modified Multi Class Association Rule Method.The method is based on Associative Classification which combines classification with association rule discovery. …”
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  6. 6
    A Critical Review on Selected Fuzzy Min-Max Neural Networks and Their Significance and Challenges in Pattern Classification

    A Critical Review on Selected Fuzzy Min-Max Neural Networks and Their Significance and Challenges in Pattern Classification by Alhroob, Essam, Mohammed, Mohammed Falah, Lim, Chee Peng, Tao, Hai

    Published 2019
    “…FMM is considered one of the most useful neural networks for pattern classification. …”
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  7. 7
    A new feature-based wavelet completed local ternary pattern (FEAT-WCLTP) for texture and medical image classification

    A new feature-based wavelet completed local ternary pattern (FEAT-WCLTP) for texture and medical image classification by Shamaileh, Abeer Moh'd Salem

    Published 2019
    “…Nowadays, texture image descriptors are used in many important real-life applications. The use of texture analysis in texture and medical image classification has attracted considerable attention. …”
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  8. 8
    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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  9. 9
    Thresholding and Fuzzy Rule-Based Classification Approaches in Handling Mangrove Forest Mixed Pixel Problems Associated with in QuickBird Remote Sensing Image Analysis

    Thresholding and Fuzzy Rule-Based Classification Approaches in Handling Mangrove Forest Mixed Pixel Problems Associated with in QuickBird Remote Sensing Image Analysis by Mohd, Othman *, Nanna , Suryanna, Sahib@Sahibuddin, Shahrin, Abdollah, Mohd Faizal, Selamat, Siti Rahayu

    Published 2012
    “…Therefore, the aim of this research is to obtain the optimal threshold value for each class of landuse/landcover using a combination of thresholding and fuzzy rule-based classification techniques. …”
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  10. 10
    Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification

    Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification by Navan, Farhad Pourpanah

    Published 2015
    “…The outcomes indicate the effectiveness of QFAM-based models in tackling pattern classification tasks. …”
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  11. 11
    Flexible enhanced fuzzy min–max neural network model for pattern classification problems

    Flexible enhanced fuzzy min–max neural network model for pattern classification problems by Al-Hroob, Essam Muslem Harb

    Published 2020
    “…The results demonstrate the efficiency of FEFMM in handling pattern classification problems and providing a superior performance of classification accuracy as compared to the other network structures from the same variants such as EFMM, FMM variants and also non-FMM related models. …”
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  12. 12
    Biceps brachii surface EMG classification using neural networks

    Biceps brachii surface EMG classification using neural networks by Chong, Yee Lin

    Published 2012
    “…With these satisfactory results, the effectiveness of the proposed classifiers in EMG pattern classification problem is proven.…”
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  13. 13
    Recognizing Patterns of Music Signals to Songs Classification Using Modified AIS-Based Classifier

    Recognizing Patterns of Music Signals to Songs Classification Using Modified AIS-Based Classifier by Muda, N. A., Ahmad, S., Muda, A. K.

    Published 2011
    “…The aim of this research is to investigate Artificial Immune System (AIS) domain by focusing on the modified AIS-based classifier to solve this problem where the focuses are the censoring and monitoring modules. …”
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  14. 14
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The extraction network extracts detectors that represent pattern’s classes to be supplied to the classification network. …”
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  15. 15
    An improved multiple classifier combination scheme for pattern classification

    An improved multiple classifier combination scheme for pattern classification by Abdullah,

    Published 2015
    “…Combining multiple classifiers are considered as a new direction in the pattern recognition to improve classification performance. …”
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  16. 16
    Evaluation and optimization of frequent association rule based classification

    Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

    Published 2014
    “…Problems such as the discovery of random and coincidental patterns or patterns with no significant values, and the generation of a large volume of rules from a database commonly occur. …”
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  17. 17
    Rough Set Discretize Classification of Intrusion Detection System

    Rough Set Discretize Classification of Intrusion Detection System by Noor Suhana, Sulaiman, Rohani, Abu Bakar

    Published 2016
    “…Many pattern classification tasks confront with the problem that may have a very high dimensional feature space like in Intrusion Detection System (IDS) data. …”
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  18. 18
    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
    “…Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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  19. 19
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…Several approaches have been devoted to study such problems using linear and non-linear classification rules, but limited to group imbalance rather than the combination of both problems. …”
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  20. 20
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…On top of that, random forest ensemble classifier model has reported successive perform in most classification and pattern recognition problems. The expanding of randomness layer in the traditional decision tree is able to increase the diversity of classification accuracy. …”
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