Sentence examples for credit prediction from inspiring English sources

Eventually, the FAST (Fourier Amplitude Sensitivity Test) method is proved to generate the most appropriate weighting system considering the consistence of the credit prediction with the traditional whole building simulation approach.

As an important future direction, everyone would expect that improving the data analytical framework will increase credit prediction correctness.

The experimental results over nine real-life data sets show that the associative memory here proposed constitutes an appropriate solution for bankruptcy and credit risk prediction, performing significantly better than the rest of models under class imbalance and data overlapping conditions in terms of the true positive rate and the geometric mean of true positive and true negative rates.

Additionally, existing studies fully proved that ANNs perform better than statistical models for credit risk prediction (Yim and Mitchell 2005; Wilson and Sharda 1994; Back et al. 1996).

Moreover, the explanatory variables (or evaluation indexes) play an important role in credit rating prediction and vary across different target agents.

First, the data preparation process, such as data collection, variable selection, and data cleaning for credit scoring prediction can help reduce noise levels and further enhance the evaluation accuracy of credit risk.

The technique approach 100Credit took allowed them to deliver high-quality credit rating predictions.

Duffee and Zhou 2001 compared the effects of firm attributes and external factors on credit rating predictions.

For other people, they at most have identity and demographic information (such as ID, name, age, marriage status, and education level), and it is not plausible to get reliable credit risk predictions using traditional models.

I predicted that Facebook's revenue from Payments will double every year for the next five years and still stand by that prediction – Credits or no Credits.

In addition to the accuracy of analytic results, the paper designs a misclassification cost measurement by taking the two types error and the economic sense into account, which is more suitable to evaluate the credit card churn prediction model.