Results 91 to 100 of about 45,837 (241)
ENHANCED ALGORITHMS FOR MINING OPTIMIZED POSITIVE AND NEGATIVE ASSOCIATION RULE FROM CANCER DATASET
ICTACT Journal on Soft Computing, 2018 The most important research aspect nowadays is the data. Association rule mining is vital mining used in data which mines many eventual informations and associations from enormous databases.
I Berin Jeba Jingle, J Jeya ACelin
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arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]
Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Bettina Grün +2 more
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Reconstructing thicket clump formation using association rules analysis
Journal of Vegetation Science, Volume 35, Issue 3, May/June 2024.Association rules (or market basket) analysis was effective in eliciting common associations between species and size classes across different stages of thicket clump formation in a savanna. Vachellia karroo established alone in open grassland, whereas a suite of clump‐initiating species recruited in close association with large V.
Rhys Nell +2 more
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IET Intelligent Transport Systems, Volume 18, Issue 3, Page 517-527, March 2024.Abstract This study aims to explore the relationship between traffic flow states and crash type/severity in the scenarios of normal crashes, primary crashes, and secondary crashes using the association rules mining approach. The crash data and real‐time traffic data were collected from the I‐880 freeway for five years in California, USA.
Bo Yang +4 more
wiley +1 more source
DLLog: An Online Log Parsing Approach for Large‐Scale System
International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.Syslog is a critical data source for analyzing system problems. Converting unstructured log entries into structured log data is necessary for effective log analysis. However, existing log parsing methods demonstrate promising accuracy on limited datasets, but their generalizability and precision are uncertain when applied to diverse log data ...
Hailong Cheng +4 more
wiley +1 more source
A Fast Approach for Up-Scaling Frequent Itemsets
IEEE Access, 2020 With the rapid growth of data scale and diversification of demand, people have an urgent desire to extract useful frequent itemset from datasets of different scales. It is no doubt that the traditional method can solve the problem.
Runzi Chen, Shuliang Zhao, Mengmeng Liu
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FREQUENT ITEMSETS MINING FOR BIG DATA
, 2019 Frequent Itemsets Mining (FIM) is a fundamental mining model and plays an important role in Data Mining. It has a vast range of application fields and can be employed as a key calculation phase in many other mining models such as Association Rules, Correlations, Classifications, etc. Generally speaking, FIM counts the frequencies of co-occurrence items,
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Frequent Itemset Mining in Big Data With Effective Single Scan Algorithms
IEEE Access, 2018 This paper considers frequent itemsets mining in transactional databases. It introduces a new accurate single scan approach for frequent itemset mining (SSFIM), a heuristic as an alternative approach (EA-SSFIM), as well as a parallel implementation on ...
Youcef Djenouri +3 more
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Characterizing Transactional Databases for Frequent Itemset Mining
, 2019 This paper presents a study of the characteristics of transactional databases used in frequent itemset mining. Such characterizations have typically been used to benchmark and understand the data mining algorithms working on these databases. The aim of our study is to give a picture of how diverse and representative these benchmarking databases are ...
Lezcano Ríos, Christian Gerardo +1 more
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PLoS ONE, 2015 Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples.
Ujjwal Maulik +3 more
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