Communications Biophysics

Contains research objectives and reports on three research projects.National Institutes of Health (Grant MH-04737-05)National Institutes of Health (Grant NB-05462-02)Joint Services Electronics Programs (U.S. Army, U.S. Navy, and U.S. Air Force) under Contract DA 36-039-AMC-03200(E)National Science Foundation (Grant GP-2495)National Aeronautics and Space Administration (Grant NsG-496

Daily Eastern News: August 06, 1958

https://thekeep.eiu.edu/den_1958_aug/1000/thumbnail.jp

Logistic Regression or Neural Network? Which Provides Better Results for Retail Loans?

While there is a large literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in our country, where there is not much scientific work on this topic. Recognising who is becoming a bad debtor is not easy. There are several ways to analyse the data, which may even show different results. In this paper, my aim is to predict the default of household loans using logistic regression and neural networks. The question is, which method produces the better results

Logistic Regression or Neural Network? Which Provides Better Results for Retail Loans?

While there is a large literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in our country, where there is not much scientific work on this topic. Recognising who is becoming a bad debtor is not easy. There are several ways to analyse the data, which may even show different results. In this paper, my aim is to predict the default of household loans using logistic regression and neural networks. The question is, which method produces the better results

Logistic Regression or Neural Network? Which Provides Better Results for Retail Loans?

While there is extensive literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in Hungary. Recognising who is at risk of becoming a bad debtor is not easy. There are several ways to analyse the data, which may yield different results. In this paper, my aim is to predict the default of household loans using logistic regression and neural networks. The question is, which method produces the better results?The analyses show that the neural network model produced the best and most favourable results. The accuracy of the best method was found to be 81.5%

Legalizing gaming in Singapore: The ethical implications

In this day and age when directors of companies are found to be corrupt and governments are not void of graft and bribes, it is not a wonder that people would question the integrity of both companies and governments. Many cities in the world have decided to build mega resorts with gaming facilities for the purpose of economic development that includes employment and tourism. The aim of this study therefore is to contrast and compare the ethical issues and implications of the decisions made not only by the Singapore government but other governments of the US, Macau, the Bahamas and Australia to open casino-based resorts in their countries. In addition to also determine if the decision to legalize and build the Integrated Resorts in Singapore was for the greater good and therefore ethical