Relevance of Frequent Pattern (FP)-Growth-Based Association Rules on Liver Diseases

Patel, Punyaban; Sivaiah, Borra; Patel, Riyam

doi:10.1007/978-981-19-0901-6_58

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Cited by 3 publications

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“…1. Every algorithm uses its own data type to get optimal clusters or results [49]. In any Clustering Algorithm used to differentiate between one cluster group with other cluster group [56].…”

Section: Notementioning

confidence: 99%

A Survey on Dependency of Parallel Clustering Platforms on Clustering Algorithms with Their Clustering Criteria for Big Data

Prasad,

Thota

2023

Preprint

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Clustering is a data mining task used for the data extraction from the data bases or files. Clustering is used to find unknown groups present in the data sources like files or data bases. This paper focuses on clustering algorithms performance dependency on the parallel clustering platforms and the clustering algorithms along with their clustering criteria. The problems with the present Traditional clustering algorithms were throughput and data source size changes (scalability). So they can’t address the big data. So for handling the huge volumes of data, parallel clustering algorithms along with clustering criteria were used. For processing the big Data Parallel clustering algorithms are of two types based on computing platforms used. They were the horizontal scaling platforms and vertical scaling platforms.

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Section: Notementioning

confidence: 99%