ISSN: 2349-5162

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Published in:

Volume 5 Issue 2
February-2018
eISSN: 2349-5162

Unique Identifier

JETIR1802047

Page Number

302-305

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Title

Analysis of German credit data using microsoft azure analytics

ISSN

2349-5162

Cite This Article

"Analysis of German credit data using microsoft azure analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 2, page no.302-305, February-2018, Available :http://www.jetir.org/papers/JETIR1802047.pdf

Abstract

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

Cite This Article

"Analysis of German credit data using microsoft azure analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp302-305, February-2018, Available at : http://www.jetir.org/papers/JETIR1802047.pdf

Publication Details

Published Paper ID: JETIR1802047
Registration ID: 171251
Published In: Volume 5 | Issue 2 | Year February-2018
DOI (Digital Object Identifier): http://doi.one/10.1717/JETIR.17318
Page No: 302-305
ISSN Number: 2349-5162

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Cite This Article

"Analysis of German credit data using microsoft azure analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp302-305, February-2018, Available at : http://www.jetir.org/papers/JETIR1802047.pdf




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