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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP8039

LOAN AMOUNT ANALYSIS AND PREDICTION USING MACHINE LEARNING

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-

Subject:

-

Paper ID:

IJSREMWP8039

Volume:

8 |

7 |

Jul 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MKM

Manoj K M

DGM

Dr. Geetha M

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Abstract

This research paper presents a comprehensive analysis and prediction of loan sanction amounts using multiple machine learning models. The dataset includes various customers attributes such as income, expenses, credit score, and employment type. We preprocess the data, perform exploratory data analysis (EDA) [1], and evaluate the performance of several regression models, including Linear Regression, Bagging Regressor, Decision Tree Regressor, and Random Forest Regressor.

KEYWORDS

Linear Regression Bagging Regression Decision Tree Random Forest Regression.

Cite This Article

Manoj K M, Dr. Geetha M, "LOAN AMOUNT ANALYSIS AND PREDICTION USING MACHINE LEARNING," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024.

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12/31/45482

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The authors declare no conflict of interest related to this research work.

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