Pages that link to "Item:Q1579020"

The following pages link to Neural network credit scoring models (Q1579020):

Displaying 39 items.

• Loan origination decisions using a multinomial scorecard (Q338917) (← links)
• Weight-selected attribute bagging for credit scoring (Q473541) (← links)
• Credit scoring using support vector machines with direct search for parameters selection (Q1006913) (← links)
• Diversity of ability and cognitive style for group decision processes (Q1010126) (← links)
• Modelling credit rating by fuzzy adaptive network (Q1029195) (← links)
• Support vector machines for default prediction of SMEs based on technology credit (Q1038344) (← links)
• A comparison of neural networks and linear scoring models in the credit union environment (Q1278359) (← links)
• Neural networks in business: Techniques and applications for the operations researcher (Q1579010) (← links)
• Credit rating using type-2 fuzzy neural networks (Q1718436) (← links)
• Predicting repayment of the credit card debt (Q1762040) (← links)
• Machine learning for credit scoring: improving logistic regression with non-linear decision-tree effects (Q2060438) (← links)
• Risk analysis via Łukasiewicz logic (Q2156531) (← links)
• Credit scoring based on the set-valued identification method (Q2220404) (← links)
• Updating a credit-scoring model based on new attributes without realization of actual data (Q2256179) (← links)
• Mining the customer credit using classification and regression tree and multivariate adaptive regression splines (Q2257606) (← links)
• Sparse multi-criteria optimization classifier for credit risk evaluation (Q2317624) (← links)
• Neural network ensemble strategies for financial decision applications (Q2387272) (← links)
• Two-stage genetic programming (2SGP) for the credit scoring model (Q2489349) (← links)
• The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing (Q2497261) (← links)
• Credit risk evaluation using multi-criteria optimization classifier with kernel, fuzzification and penalty factors (Q2514835) (← links)
• Recent developments in consumer credit risk assessment (Q2643976) (← links)
• A novel dynamic credit risk evaluation method using data envelopment analysis with common weights and combination of multi-attribute decision-making methods (Q2668640) (← links)
• Integrating data augmentation and hybrid feature selection for small sample credit risk assessment with high dimensionality (Q2676331) (← links)
• Credit scoring with drift adaptation using local regions of competence (Q2677348) (← links)
• Modeling company failure: a longitudinal study of Turkish banks (Q2926495) (← links)
• Using supervised kernel locality preserving projections to improve classifier performance on credit rating forecasting (Q3020601) (← links)
• A classification spline machine for building a credit scorecard (Q3638578) (← links)
• Benchmarking state-of-the-art classification algorithms for credit scoring (Q4661113) (← links)
• (Q4969087) (← links)
• A new mixture cure model under competing risks to score online consumer loans (Q5234356) (← links)
• Can machine learning approaches predict corporate bankruptcy? Evidence from a qualitative experimental design (Q5234381) (← links)
• Ensembles of Classifiers in Arrears Management (Q5302330) (← links)
• An application of locally linear model tree algorithm with combination of feature selection in credit scoring (Q5499826) (← links)
• Advances in Neural Networks – ISNN 2005 (Q5707241) (← links)
• Application of credit‐scoring methods in a decision support system of investment for peer‐to‐peer lending (Q6056292) (← links)
• Machine learning in corporate credit rating assessment using the expanded audit report (Q6097105) (← links)
• A data-driven explainable case-based reasoning approach for financial risk detection (Q6158390) (← links)
• Cost-sensitive thresholding over a two-dimensional decision region for fraud detection (Q6179994) (← links)
• Lost in a black-box? Interpretable machine learning for assessing Italian SMEs default (Q6581548) (← links)