UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 3 | March 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 4 Issue 7
July-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR1707040


Registration ID:
215722

Page Number

222-228

Share This Article


Jetir RMS

Title

Effective FrameworkwithFinite ClientTransferDatasetfor Weather Predictionusing Data Mining Techniques

Abstract

The importance of big data insiststhe data sets that are so large in such a way that traditional data processing applications are not enough to process it. In order to get the necessary information from the big data, there is a need for classification technique and also we use techniques for prediction using those data sets. Here the classification is done by two different algorithms namely C5.0 and SVC (Support Vector Clustering) algorithm, where both of them are combined in proposed work to give efficient results in classification of the required data sets. C5.0 is an algorithm used to generate a decision tree which is used for classification, and for this reason it is often refer to as a statistical classifier. It performs winnowing in such a way that the decision tree becomes more accurate and removes the attributes which may be unhelpful. The SVC is a statistics clustering algorithm that does not make any presumption on the number of the clusters in the data. The performance of both classifiers was monitored and analyzed. The result of the proposed work shows better classification when compared to the single use C5.0 classifier. The future weather predictions are also been calculated and saved in the form of dataset virtualization.

Key Words

C5.0; SVC algorithm; Winnowing; partitioning

Cite This Article

"Effective FrameworkwithFinite ClientTransferDatasetfor Weather Predictionusing Data Mining Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 7, page no.222-228, July-2017, Available :http://www.jetir.org/papers/JETIR1707040.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Effective FrameworkwithFinite ClientTransferDatasetfor Weather Predictionusing Data Mining Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 7, page no. pp222-228, July-2017, Available at : http://www.jetir.org/papers/JETIR1707040.pdf

Publication Details

Published Paper ID: JETIR1707040
Registration ID: 215722
Published In: Volume 4 | Issue 7 | Year July-2017
DOI (Digital Object Identifier):
Page No: 222-228
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

0003152

Print This Page

Current Call For Paper

Jetir RMS