Notice Board :

Call for Paper
Vol. 4 Issue 10

Submission Start Date:
October 01, 2018

Acceptence Notification Start:
October 10, 2018

Submission End:
October 15, 2018

Final MenuScript Due:
October 25, 2018

Publication Date:
October 31, 2018


                         Notice Board: Call for PaperVol. 4 Issue 10      Submission Start Date: October 01, 2018      Acceptence Notification Start: October 10, 2018      Submission End: October 15, 2018      Final MenuScript Due: October 25, 2018      Publication Date: October 31, 2018




Volume III Issue V

Author Name
Shikha Sharma, Chetan Chauhan
Year Of Publication
2017
Volume and Issue
Volume 3 Issue 5
Abstract
Abstract:- Data Classification may be a very fashionable and computationally overpriced task. Most of those information classification techniques square measure supported the conception of call trees. several researchers have worked on the malady prediction systems exploitation the information mining techniques. a number of the systems square measure for predicting one malady and a few for the predicting the multiple diseases. Still there's scope to enhance the potency of the malady prediction. during this paper, we tend to square measure presenting associate degree updated ID3 rule. a brand new attribute choice rule has projected during this paper. The accuracy of the projected methodology is best than the present rule.
PaperID
2017/IJRRETAS/5/2017/23610

Author Name
Rahul Sharma, Prof. O.P. Sharma
Year Of Publication
2017
Volume and Issue
Volume 3 Issue 5
Abstract
In cloud computing, data is moved to a remotely located cloud server. Cloud server faithfully stores the data and return back to the owner whenever needed. Data and computation integrity and security are major concerns for users of cloud computing facilities. Today's clouds typically place centralized, universal trust in all the cloud's nodes.Hadoop is founded on MapReduce, which is among the most popular programming items for huge knowledge analysis in a parallel computing environment. In this paper, we reward a particular efficiency analysis, characterization, and evaluation of Hadoop MapReduce WordCount utility.
PaperID
2017/IJRRETAS/6/2017/24610