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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…These data are processed and stored in appropriate formats in a MySQL server database. Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  2. 2
    A frequent pattern mining algorithm based on FP-growth without generating tree

    A frequent pattern mining algorithm based on FP-growth without generating tree by Tohid, Hossein, Ibrahim, Hamidah

    Published 2010
    “…It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).…”
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  3. 3
    A frequent pattern mining algorithm based on FP-growth without generating tree

    A frequent pattern mining algorithm based on FP-growth without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2010
    “…In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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  4. 4
    Using unique-prime-factorization theorem to mine frequent patterns without generating tree

    Using unique-prime-factorization theorem to mine frequent patterns without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2011
    “…In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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  5. 5
    Selection, generation and extraction of MCCTree using XMCCTree

    Selection, generation and extraction of MCCTree using XMCCTree by Sazaly, Ummu Sulaim, Selamat, Mohd Hasan, Baharom, Salmi, A. Jabar, Marzanah

    Published 2012
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  6. 6
    A numerical method for frequent pattern mining

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…There are two new properties introduced in this method; a novel tree structure called PC_Tree and PC_Miner algorithm. …”
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  7. 7
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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  8. 8
    Extended spatial decision tree algorithm for classifying hotspot occurrence

    Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

    Published 2013
    “…The accuracy of decision tree generated by the ID3 and C4.5 algorithm is 49.02% and 65.24%, respectively. …”
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  9. 9
    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
    “…Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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  10. 10
    Comparing the knowledge quality in rough classifier and decision tree classifier

    Comparing the knowledge quality in rough classifier and decision tree classifier by Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy

    Published 2008
    “…This paper presents a comparative study of two rule based classifier; rough set (Rc) and decision tree (DTc).Both techniques apply different approach to perform classification but produce same structure of output with comparable result. …”
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  11. 11
    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang

    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

    Published 2013
    “…Therefore new sets of invariant algorithms have been proposed to resolve the above mentioned issues. …”
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  12. 12
    An optimized attack tree model for security test case planning and generation

    An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

    Published 2018
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  13. 13
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  14. 14
    Data Classification and Its Application in Credit Card Approval

    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…The result of this application using the sample credit card approval dataset includes a decision tree, a set of rules derived from the decision tree and its accuracy. …”
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  15. 15
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  16. 16
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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  17. 17
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, N., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. …”
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  18. 18
    Using modification of Prim's algorithm and GNU Octave and to solve the multiperiods installation problem

    Using modification of Prim's algorithm and GNU Octave and to solve the multiperiods installation problem by ,, Wamiliana, Usman, Mustofa, ,, Warsono, Daoud, Jamal Ibrahim

    Published 2020
    “…, and that name is chosen because it is like Unix but differs from Unix because it is free and contains no Unix code. Those algorithms were implemented using 300 randomly generated problems. …”
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  19. 19
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, Norwati, Sulaiman, Md. Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2002
    “…Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. …”
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  20. 20
    Classification with degree of importance of attributes for stock market data mining

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The predictive FDT has been tested using three data sets including KLSE, NYSE and LSE. The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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