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  1. 1

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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    Thesis
  2. 2

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

    Published 2022
    “…One common problem in pattern recognition is dealing with multidimensional data, which is prominent in studies involving spectral data such as ultraviolet visible (UV/Vis), infrared (IR), and Raman spectroscopy data. …”
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    Article
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    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The experimental results on artificial data sets and real-world data sets (from UCI Repository) show that the new method could improve both the efficiency and accuracy of pattern classification. …”
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  5. 5

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

    Published 2016
    “…Although previous work proved that Associative Classification produces better classification accuracy compared to typical classifiers, the study on applying Associative Classification to solve text classification problem are limited due to the common problem of high dimensionality of text data and this will consequently results in exponential number of generated classification rules. …”
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  6. 6

    An artificial neural network for pattern classification and visualization by Sandra,, Ong Pi Yin.

    Published 2010
    “…Today, ANN has proven to be able to im itate the human neural network and perform task such as solving real world problems. This study aims to explore in detail an ANN model that is able to perform the task of pattern classification and visualisation , and as well as to evaluate the performance of this model. …”
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    Final Year Project Report / IMRAD
  7. 7

    A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

    Published 2010
    “…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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  8. 8

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

    Published 2011
    “…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. …”
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  9. 9

    Novel Art-Based Neural Network Models For Pattern Classification, Rule Extraction And Data Regression by Yap , Keem Siah

    Published 2010
    “…This thesis is concerned with the development of novel neural network models for tackling pattern classification, rule extraction, and data regression problems. …”
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  10. 10

    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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    Thesis
  11. 11

    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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    Article
  12. 12

    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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  13. 13

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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    Development of a prototype application to detect bad behaviour pattern / Mohamad Khairul Firdhaus M. Dollah by M. Dollah, Mohamad Khairul Firdhaus

    Published 2008
    “…Bad behaviour can be prevented by knowing their behaviour patterns before the problem occurs. Data mining is one way that can help in predicting or identifying the patterns behavior of certain individual that is involved in terrorist activity. …”
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    Integrative gene selection for classification of microarray data by Ong, Huey Fang, Mustapha, Norwati, Sulaiman, Md. Nasir

    Published 2011
    “…Microarray data classification is one of the major interests in health informatics that aims at discovering hidden patterns in gene expression profiles. …”
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    Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

    Published 2023
    “…The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering. � 2006 IEEE.…”
    Article
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    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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    A flexible enhanced fuzzy min-max neural network for pattern classification by Alhroob, Essam, Mohammed, Mohammed Falah, Al Sayaydeh, Osama Nayel, Hujainah, Fadhl, Ngahzaifa, Ab Ghani, Lim, Chee Peng

    Published 2024
    “…The performance of the proposed model is evaluated with benchmark data sets. The results demonstrate its efficiency in handling pattern classification tasks, outperforming other related models in online learning environments.…”
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