基于Map reduce框架的大数据混合分类器模型

IF 0.4 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Data Mining Modelling and Management Pub Date : 1900-01-01 DOI:10.1504/ijdmmm.2024.10057054

A. K. Prasad, Venkat Dass M, Sudheer Reddy K., Sitha Ramulu V, K. R. Prasad

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Hybrid Classifier Model for Big Data by leveraging Map reduce framework

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来源期刊

International Journal of Data Mining Modelling and Management COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

1.10

自引率

0.00%

发文量

期刊介绍： Facilitating transformation from data to information to knowledge is paramount for organisations. Companies are flooded with data and conflicting information, but with limited real usable knowledge. However, rarely should a process be looked at from limited angles or in parts. Isolated islands of data mining, modelling and management (DMMM) should be connected. IJDMMM highlightes integration of DMMM, statistics/machine learning/databases, each element of data chain management, types of information, algorithms in software; from data pre-processing to post-processing; between theory and applications. Topics covered include: -Artificial intelligence- Biomedical science- Business analytics/intelligence, process modelling- Computer science, database management systems- Data management, mining, modelling, warehousing- Engineering- Environmental science, environment (ecoinformatics)- Information systems/technology, telecommunications/networking- Management science, operations research, mathematics/statistics- Social sciences- Business/economics, (computational) finance- Healthcare, medicine, pharmaceuticals- (Computational) chemistry, biology (bioinformatics)- Sustainable mobility systems, intelligent transportation systems- National security