FEATURE CLUSTERING USING SUBSELECTION ALGORITHM IN BIG DATA USING FIDOOP
Journal Title: International Research Journal of Computer Science - Year 2016, Vol 0, Issue 0
Abstract
Big data processing is a high demand area which imposes a heavy burden on computation, communication, storage in data centers, which incurs considerable operational cost to data center provider. So minimizing cost has become an issue for the upcoming big data. Different from conventional cloud service one of the main feature of the big data service is the tight coupling between data and computation, as computation task can be conducted only when the corresponding data are available. As a result, three factors that is communicational cost, computational cost, operational cost effects the expenditure cost of data centers. So in order to minimize the cost clustering is used. Clustering groups a selected objects into classes of similar objects. Feature Selection Removes Irrelevant Features- it occurs in the batch processing (scheduling algorithm) Redundant Features its occurs in the cluster formation (data-centric algorithm) jointoptimization– 2 steps Features divided into clusters(subsets) MST Cluster representatives are selected Efficient, Effective, Independent. Based on these criteria, a feature clustering based on selection algorithm is proposed and experimentally evaluated for a sample cancer dataset. This work finds the effective attributes used and removes redundancy.
Authors and Affiliations
Surekha C. , Vijayalakshmi S. , Natteshan N. V. S
Keywords
Related Articles
- EP ID EP180576
- DOI -
- Views 99
- Downloads 0
Parameter Adjustment of Pulse Coupled Neural Networks Based on White Pixels Evaluation
This paper presents a new method to automatic stop the iteration of Pulse Coupled Neural Networks. (PCNN) by evaluating the numbers of white pixels. The PCNN is used to segment the image which has object and background....
Block Based Algorithms for Estimating Motion
In this paper we are discussing about ME in video compression that to specifically about the algorithms used for it. Here we can see the different types of BMA which are implemented and compared, which includes from some...
Simplified CVSS 2.0 for End User and Development team
The CVSS 2.0 aims at generating the Score for the vulnerability which occurs whiles the development process or after the development of the software. These vulnerabilities may prove to be a threat when the software is re...
Integrity Preserving Outsourcing Model in Cloud with Proxy Based Public Auditing
Cloud computing is the long dreamed vision of computing as a utility, where data owners can remotely store their data in the cloud to enjoy on-demand high-quality applications and services. Secured data storage and retri...
Angular Paging in Distance-based Location Registration in Mobile Communication
In this study, we proposed a new paging method, angular paging, that reduces the paging cost in distance based location registration (DBR). DBR causes a mobile station (MS) to register its location when the distance betw...