Data mining techniques and algorithms in cloud environment a review

Abstract

Cloud Computing is resourceful in which computing resources are made available on-demand to the user as needed. Data mining is a process of discovering interesting patterns from a large amount of data. The difficulty is in collecting these data and carrying out computations to get the significant information. Data mining techniques and applications can be effectively used in cloud computing environment. Data mining and the cloud computing are considered as major technologies. The data mining in cloud computing allows organizations to centralize the management of software and data storage. This paper provides a review of various data mining techniques and different types of algorithms in cloud computing which can be used for resource sharing.

A Euclidean Group Assessment on Semi-Supervised Clustering for Healthcare Clinical Implications Based on Real-Life Data

“…Gregory Piatetsky stated in the Knowledge Discovery (KDD) conference: “Weka is a landmark system in data mining and machine learning history for the research communities, cause it holds the toolkit that has undoubtedly gained such extensive espousal and survived for a prolonged period. [15]” There was substantial attention paid to the determination of how distinctive clustering techniques were utilized in different areas of the environment [16,17,18,19,20] and in the healthcare sector for different disease predictions [21,22,23,24,25,26,27,28,29,30,31,32]. In addition, K-mean and SOM (self-organizing map) were used in this study for grouping the clusters of the real-life diabetes dataset, after careful analysis by the literature.…”