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  1. 1
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  2. 2
    An efficient and effective case classification method based on slicing

    An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

    Published 2006
    “…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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  3. 3
    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
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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  4. 4
    An adaptive ant colony optimization algorithm for rule-based classification

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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  5. 5
    Enhanced ontology-based text classification algorithm for structurally organized documents

    Enhanced ontology-based text classification algorithm for structurally organized documents by Oleiwi, Suha Sahib

    Published 2015
    “…The third algorithm is the Ontology Based Text Classification (OBTC) and is designed to reduce the dimensionality of training sets. …”
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  6. 6
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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  7. 7
    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH

    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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  8. 8
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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  9. 9
    Multi-label learning based on positive label correlations using predictive apriori

    Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

    Published 2019
    “…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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  10. 10
    Ideal combination feature selection model for classification problem based on bio-inspired approach

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. The next step is to define an optimized feature set for classification task. …”
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  11. 11
    Mutable composite firefly algorithm for gene selection in microarray based cancer classification

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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  12. 12
    Knowledge base processing method based on text classification algorithm

    Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

    Published 2023
    “…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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  13. 13
    Genetic algorithm based ensemble framework for sentiment analysis

    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…Methods of feature extraction can be separated into word based and phrase based. Phrase based features generally performed better, however the feature sets they produce are much larger than word based but this is where feature selection is helpful. …”
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  14. 14
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…In this thesis, a new method known as Grid Based Classifier was proposed. This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  15. 15
    Grid base classifier in comparison to nonparametric methods in multiclass classification

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…In this paper, a new method known as Grid Base Classifier was proposed. This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  16. 16
    An ensemble data summarization approach based on feature transformation to learning relational data

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…A ensemble clustering is designed, used and evaluated to generate the final classification framework that will take all input generated from the GA based clustering with Feature Selection and Feature Construction algorithms and perform the classification task for the relational datasets. …”
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  17. 17
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. …”
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  18. 18
    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review

    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
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  19. 19
    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification

    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

    Published 2016
    “…Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. …”
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  20. 20
    A survey : particle swarm optimization-based algorithms for grid computing scheduling systems.

    A survey : particle swarm optimization-based algorithms for grid computing scheduling systems. by Ambursa, Faruku Umar, Latip, Rohaya

    Published 2013
    “…Meta task-based and workflow-based are the main categories explored. …”
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