Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This project's objective is to create a machine learning model that forecasts loan acceptance based on a variety of characteristics of loan applicants, including their credit history, income, employment status, etc. The model is trained on a dataset of past loan applications, and several measures, including accuracy, precision, recall, and F1-score, are used to assess its performance. As a result of the findings, financial institutions can automate the loan approval process and lower the risk of default by using the model to anticipate loan acceptance with accuracy.
"Loan Approval Prediction", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.955 - 958, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304154.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator