A MapReduce solution for associative classification of big data
Associative classifiers have proven to be very effective in classification problems.
Unfortunately, the algorithms used for learning these classifiers are not able to adequately …
Unfortunately, the algorithms used for learning these classifiers are not able to adequately …
[PDF][PDF] Parallel implementation of apriori algorithms on the Hadoop-MapReduce platform-an evaluation of literature
Data mining is the extraction of useful, prognostic, interesting, and unknown information from
massive transaction databases and other repositories. Data mining tools predict potential …
massive transaction databases and other repositories. Data mining tools predict potential …
Deep parallelization of parallel FP-growth using parent-child MapReduce
MapReduce is an important programming model for processing in distributed environments.
Compared to other distributed programming models, MapReduce reduces communication …
Compared to other distributed programming models, MapReduce reduces communication …
Data mining technique for reduction of association rules in distributed system
B Waghamare, Y Bodhe - 2016 International Conference on …, 2016 - ieeexplore.ieee.org
In today's world, there are number of transactions can be performed on social media. In such
distributed environment where timely accessing of data is important, it becomes difficult to …
distributed environment where timely accessing of data is important, it becomes difficult to …
[PDF][PDF] An efficient parallel association rule mining algorithm based on MapReduce framework
B Singh, R Miri - International Journal of Engineering Research, 2016 - academia.edu
Data mining is an important field in Technology world. Association rules are a must and
important step to discuss the data mining and inside findings of the relation between data …
important step to discuss the data mining and inside findings of the relation between data …
Paths sharing based FP-growth data mining algorithms
S Ji, D Zhang, L Zhang - 2016 8th International Conference on …, 2016 - ieeexplore.ieee.org
Due to the network alarm data in cloud environment has the characteristics of massive,
redundancy, relevance, etc., traditional FP-Growth algorithm has memory and computing …
redundancy, relevance, etc., traditional FP-Growth algorithm has memory and computing …
Parallel Implantation of Frequent Itemset Mining Using Inverted Matrix Based on OpenCL
P Zala, H Kotadiya, S Bhanderi - Proceedings of the International …, 2016 - Springer
Extracting knowledge in the form of frequent itemsets and association rules deserves great
importance in the field of data mining. Apriori algorithm suffers from multiple scans of the …
importance in the field of data mining. Apriori algorithm suffers from multiple scans of the …