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  1. 1
    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP

    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP by Saputra, Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Mining Of Resource Usage Using Evoc Algorithm In Grid Environment.

    Mining Of Resource Usage Using Evoc Algorithm In Grid Environment. by Kee, Sim Ee, Chan, Huah Yong, Haron, Fazilah

    Published 2007
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  4. 4
    A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi

    A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi by Nassirtoussi, Arman Khadjeh

    Published 2015
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  5. 5
    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
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  6. 6
    Adaptive parameter control strategy for ant-miner classification algorithm

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
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  7. 7
    The disruptometer: an artificial intelligence algorithm for market insights

    The disruptometer: an artificial intelligence algorithm for market insights by Wan Nordin, Mimi Aminah, Vedenyapin, Dmitry, Alghifari, Muhammad Fahreza, Gunawan, Teddy Surya

    Published 2019
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  8. 8
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
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  9. 9
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  10. 10
    Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure

    Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

    Published 2011
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  11. 11
    A direct ensemble classifier for imbalanced multiclass learning

    A direct ensemble classifier for imbalanced multiclass learning by Sainin, Mohd Shamrie, Alfred, Rayner

    Published 2012
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  12. 12
    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks

    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
    “…Experiment results on several multimedia applications have shown that the proposed algorithm is competitive compared with the other single-view feature selection algorithms.…”
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  13. 13
    A False Alert Reduction And An Alert Score Assessment Framework For Intrusion Alerts

    A False Alert Reduction And An Alert Score Assessment Framework For Intrusion Alerts by Al-Saedi, Karim Hashim Kraidi

    Published 2013
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  14. 14
    Evaluation and optimization of frequent, closed and maximal association rule based classification

    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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  15. 15
    Study of B40 schoolchildren lifestyles and academic performance using association rule mining

    Study of B40 schoolchildren lifestyles and academic performance using association rule mining by Puteri NE Nohuddin, Zuraini Zainol, Mohd Hanafi Ahmad Hijazi

    Published 2021
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  16. 16
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  17. 17
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…The framework consists of two stages: the preprocessing stage and the stream clustering stage. …”
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  18. 18
    An Automated System For Classifying Conference Papers

    An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

    Published 2021
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  19. 19
    Improving Extreme Programming Framework With Security Concerns For E-Commerce Applications

    Improving Extreme Programming Framework With Security Concerns For E-Commerce Applications by Bala, Musa Shuaibu

    Published 2024
    thesis::doctoral thesis
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  20. 20
    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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