The novelty of the technique is that it results in a highly accurate model using RF classification technique as it is based on both exploratory data analysis as well as attributes of client. Its accuracy can be found to be more than many of the existing RF approaches.Anand, Rohit...
Machine Learning Based Loan Allocation Prediction System For Banking Sector 作者: Sinha J.;Astya R.;Tripathi K.;Verma A.;Verma M.;摘要: Banking sector in India is overwhelmed with numerous applications by individual customers or organizations for different types of loans. Every year, we hear ...
The Challenges of Using Machine Learning in Plants and the Next Technology after Prediction Recent advances in artificial intelligence and machine learning have created a step change in how to measure human development indicators, in particular asset based poverty. The combination of satellite imagery an...
Earthquake researcher, Charlotte King, has been featured in many news reports and studied extensively by the scientific community, and is most notably famous for her accurate prediction of the famous Mount St. Helen's eruption, in SW WASHINGTON STATE, which erupted at 8:32 A.M., on May 18...
Default risk prediction and feature extraction using a penalized deep neural network 2022, Statistics and Computing Determinants of Loan Prepayment and Comparison of Machine Learning Approaches 2022, Proceedings - 2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022 View all citing ...
A cross-sectional machine learning approach for hedge fund return prediction and selection Manag. Sci., 67 (7) (2021), pp. 4577-4601 CrossrefView in ScopusGoogle Scholar Wagenvoort et al., 2011 R. Wagenvoort, A. Ebner, M.M. Borys A factor analysis approach to measuring European loan an...
Earthquake researcher, Charlotte King, has been featured in many news reports and studied extensively by the scientific community, and is most notably famous for her accurate prediction of the famous Mount St. Helen's eruption, in SW WASHINGTON STATE, which erupted at 8:32 A.M., on May 18...
The accuracy of these methods will also be tested using metrics like log loss, Jaccard similarity coefficient and F 1 Score. These metrics are compared to determine the accuracy of prediction. This can help banks conserve their manpower and fiscal resources by reducing the number of steps they ...
Machine learningLoan predictionBankingDecision treeKNNLoan business is one of the major income sources for bank. Loan default problem is a major issue for loan business. Loans, specifically whether borrowers repay the loan or default on it, have a significant impact on a bank's profitability. By...
PREDICTION OF LOAN APPROVAL USING MACHINE LEARNING ALGORITHM: A REVIEW PAPERRutika Pramod KatheSakshi Dattatray PanhalePooja Prakash AvhadPunam Laxman DapseB Ghorpade DineshIJCRT(www.ijcrt.org)