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Analysis of German credit data using microsoft azure analytics

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Banking industry is a vital supply of finance in any country. Credit Risk analysis could be a essential and decisive task in banking sector. Loan sanction procedure will be followed supported the credit risk analysis of any client. Automation of deciding in money applications exploitation best algorithms and classifiers is way helpful. This work evaluates the adroitness of various Memory primarily based classifiers on credit risk analysis. The German credit information are taken for adroitness analysis and is finished exploitation open supply machine learning tool. The performances of various memory primarily based classifier square measure analyzed and a sensible guideline for choosing exceptional and compatible algorithmic rule for credit analysis is given

Key Words

German Credit Data, Azure

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"Analysis of German credit data using microsoft azure analytics", International Journal of Emerging Technologies and Innovative Research ( | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp302-305, February-2018, Available at : &

Publication Details

Published Paper ID: JETIR1802047
Registration ID: 171251
Published In: Volume 5 | Issue 2 | Year February-2018
DOI (Digital Object Identifier): 1
Page No: 302-305
ISSN Number: 2349-5162

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UGC and ISSN Approved Journal | Call For Paper
(Volume 5 | Issue 2 | February 2018 |Impact factor 5.87)

Call For Paper | Volume 5 | Issue 2 | Impact factor 5.87

Important Dates Related to Publication Procedure:
  • » Paper Submission Till: 29 February 2018.
  • » UGC and ISSN Approved Journal
  • » Review (Acceptance/Rejection) Notification: Within 02-04 Days.
  • » Paper Publish:Within 02-07 Days after submitting the all documents.
  • » Frequency: Monthly (12 issue Annually)
  • » Journal Type : Open Access
  • » Publication Charges : 1300 INR
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