"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

• venkatesh
• snehika pandey

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

German Credit Data, Azure

"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