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  Published Paper Details:

  Paper Title

Loan Approval Prediction

  Authors

  Harish P,  Surya Dharmaraj,  Dhanush K,  Punitha D

  Keywords

Logistic Regression, Decision Trees, Random Forest, Neural Networks, Xgboost , Datasets.

  Abstract


In the modern world, individuals often require financial assistance to meet their daily needs. Consequently, banks find themselves inundated with a substantial number of loan applications. Handling this influx demands significant time and manpower resources. To address this challenge, we propose the development of a predictive model that leverages a loan dataset sourced from Kaggle. This model streamlines the loan application process and provides predictions on whether a specific loan application can be approved. It employs a supervised learning algorithm, a machine learning approach, to make these predictions.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2310496

  Paper ID - 245448

  Page Number(s) - e448-e454

  Pubished in - Volume 11 | Issue 10 | October 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Harish P,  Surya Dharmaraj,  Dhanush K,  Punitha D,   "Loan Approval Prediction", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 10, pp.e448-e454, October 2023, Available at :http://www.ijcrt.org/papers/IJCRT2310496.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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