Search Results - (( using optimization method algorithm ) OR ( rule generation mining algorithm ))
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1
Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…In this method, the candidate detectors generated by particle swarm optimization form rules using apriori association rule. …”
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2
Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. …”
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3
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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4
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The mined frequent patterns are then used in generating association rules. …”
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5
A Data Mining Approach to Enhancing Birth and Death Registration Processes
Published 2025“…The optimal number of clusters of clusters for birth and death data is determined as three using elbow and silhouette validation methods. …”
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6
Direct approach for mining association rules from structured XML data
Published 2012“…The focus of this study is to propose an enhancement on memory consumption by reducing the number of candidates generated for the existing FLEX algorithm which will reduce the amount of memory needed to execute the algorithm. …”
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7
A Rough-Apriori Technique in Mining Linguistic Association Rules
Published 2008“…This paper has proposed a rough-Apriori based mining technique in mining linguistic association rules focusing on the problem of capturing the numerical interval with linguistic terms in quantitative association rules mining. …”
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Book Chapter -
8
An association rule mining approach in predicting flood areas
Published 2017“…Consequently, by using the Apriori algorithm, it generated the 10 best rules with 100% confidence level and 40% minimum support after the candidate generation and pruning technique. …”
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9
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The extraction of minimum rules operation is conducted after the default rules have been generated in order to obtain the most useful discovered rules. …”
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10
Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure
Published 2014“…This project proposed a data mining technique called Association Rule Mining. Basically Association Rule Mining is to investigate the rules according to the predefined parameter. …”
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11
Evaluation and optimization of frequent association rule based classification
Published 2014“…Works on sustaining the interestingness of rules generated by data mining algorithms are actively and constantly being examined and developed. …”
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12
Discovering association rules for mining images datasets: a proposal
Published 2005“…The Author present a data mining algorithm to find association rules in 2-dimensional colour images. …”
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13
An Association Rule Mining Approach in Predicting Flood Areas
Published 2016“…Consequently, by using the Apriori algorithm, it generated the 10 best rules with 100% confidence level and 40% minimum support after the candidate generation and pruning technique. …”
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Book Section -
14
Mining dense data: Association rule discovery on benchmark case study
Published 2016“…In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. …”
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15
HYBRID: an efficient unifying process to mine frequent itemsets
Published 2018“…Algorithms to mine frequent itemsets effectively help in finding association rules and also help in many other data mining tasks. …”
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Proceeding Paper -
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
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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Final Year Project -
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Data mining reduction methods and performances of rules
Published 2009“…In data mining the accuracy of models are associated with the strength of the rules.However, most machine learning techniques produce a large number of rules.The consequence is with large number of rules generated,processing time is much longer. …”
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18
Evaluation and optimization of frequent, closed and maximal association rule based classification
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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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
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20
Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]
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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