Search Results - (( based optimization method algorithm ) OR ( rule extraction mining algorithm ))*

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  1. 1
    Improved Malware detection model with Apriori Association rule and particle swarm optimization

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…In order to improve the detection rate of malicious application on the Android platform, a novel knowledge-based database discovery model that improves apriori association rule mining of a priori algorithm with Particle Swarm Optimization (PSO) is proposed. …”
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  2. 2
    Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm

    Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

    Published 2023
    “…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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  3. 3
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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  4. 4
    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 SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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  5. 5
    Frequent Lexicographic Algorithm for Mining Association Rules

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…The Flex algorithm and the other two existing algorithms Apriori and DIC under the same specification are tested toward these datasets and their extraction times for mining frequent patterns were recorded and compared. …”
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  6. 6
    Discovering association rules for mining images datasets: a proposal

    Discovering association rules for mining images datasets: a proposal by Hamzah, Azizi, O. K. Rahmat, Rahmita Wirza, Sulaiman, Md. Nasir

    Published 2005
    “…The Author present a data mining algorithm to find association rules in 2-dimensional colour images. …”
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  7. 7
    Improving mining efficiency: A new scheme for extracting association rules

    Improving mining efficiency: A new scheme for extracting association rules by Said, Aiman Moyaid, Dominic, P D D., Abdullah, Azween

    Published 2009
    “…In the age of information technology, the amount of accumulated data is tremendous. Extracting the association rule from this data is one of the important tasks in data mining.Most of the existing association rules in algorithms typically assume that the data set can fit in the memory.In this paper, we propose a practical and effective scheme to mine association rules from frequent patterns, called Prefixfoldtree scheme (PFT scheme).The original dataset is divided into folds, and then from each fold the frequent patterns are mined by using the tree projection approach.These frequent patterns are combined into one set and finally interestingness constraints are used to extract the association rules.The experiments will be conducted to illustrate the efficiency of our scheme.…”
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  8. 8
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…Having the ability to extract information from XML data would answer the problem of mining the web contents which is a very useful and required power nowadays. …”
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  9. 9
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…These tools are known as Data Mining (DM). One aims of DM is to discover decision rules for extracting meaningful knowledge. …”
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  10. 10
    Data mining reduction methods and performances of rules

    Data mining reduction methods and performances of rules by Ahmad, Faudziah, Basir, Mohammad Aizat

    Published 2009
    “…In summary, results show that in terms of performance of rules, Genetic Algorithm has produced the highest number of rules followed by Johnson’s Algorithm and Holte’s 1R.The best classifier for extracting rules in this study is VOT (Voting of Object Tracking).In terms of performance of rules, best results comes from rules with 30 attributes, followed by rules with 1 intersection attribute and lastly rules with 3 intersection attributes. …”
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  11. 11
    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin

    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

    Published 2006
    “…Data mining is primarily used in finance and business environment to extract knowledge from financial, retail, communication and marketing data. …”
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  12. 12
    Association Rule Mining Using Market Basket Analysis

    Association Rule Mining Using Market Basket Analysis by Nor Fadilah, Tahar @ Yusoff

    Published 2003
    “…To do the analysis, association rules mining is the popular technique for market basket analysis because of their potential in extracting rules between items in transactions. …”
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  13. 13
    Mining least relational patterns from multi relational tables

    Mining least relational patterns from multi relational tables by Selamat, Siti Hairulnita, Mat Deris, Mustafa, Mamat, Rabiei, Bakar, Zuriana Abu

    Published 2005
    “…In this paper, we propose an algorithm called Extraction Least Pattern (ELP) algorithm that using a couple of predefined minimum support thresholds. …”
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  14. 14
    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]

    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.] by Hashad, Alaa Amin, Khaw, Khai Wah, Alnoor, Alhamzah, Chew, Xin Ying

    Published 2024
    “…To address this, missing customer IDs are filled with the last valid ID, assuming repeated purchases. The FP-Growth algorithm was found to be faster and more effective than the Apriori algorithm in extracting frequent item sets and generating association rules. …”
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  15. 15
    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
    “…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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  16. 16
    A novel association rule mining approach using TID intermediate itemset

    A novel association rule mining approach using TID intermediate itemset by Aqra, Iyad, Herawan, Tutut, Norjihan, Abdul Ghani, Akhunzada, Adnan, Ali, Akhtar, Ramdan, Razali, Ilahi, Manzoor, Choo, Kim-Kwang Raymond

    Published 2018
    “…Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. …”
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  17. 17
    A novel association rule mining approach using TID intermediate itemset

    A novel association rule mining approach using TID intermediate itemset by Aqra, Iyad, Herawan, Tutut, Ghani, Norjihan Abdul, Akhunzada, Adnan, Ali, Akhtar, Bin Razali, Ramdan, Ilahi, Manzoor, Raymond Choo, Kim-Kwang

    Published 2018
    “…Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. …”
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  18. 18
    HYBRID: an efficient unifying process to mine frequent itemsets

    HYBRID: an efficient unifying process to mine frequent itemsets by Zulkurnain, Nurul Fariza, Shah, Ahmad

    Published 2018
    “…Time and space requirements for generating frequent itemsets are of utter importance. Algorithms to mine frequent itemsets effectively help in finding association rules and also help in many other data mining tasks. …”
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  19. 19
    Improved GART neural network model for pattern classification and rule extraction with application to power systems

    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
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  20. 20
    Market Basket Analysis for E-Commerce using Association Rule Mining

    Market Basket Analysis for E-Commerce using Association Rule Mining by Kayalvily, Tabianan*, Sarasvathi, Nahalingham*, Leong, Kai Cheng*

    Published 2020
    “…The author has developed an ecommerce system which has back-end system to display the performance of the product and using Association Rule Mining on the datasets. By using this system, they can know the hidden product relationships which product has the potential to be purchase together. …”
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