Pages that link to "Item:Q3114837"
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The following pages link to Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation (Q3114837):
Displaying 36 items.
- A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (Q138141) (← links)
- Supervised classification and mathematical optimization (Q339559) (← links)
- Preference disaggregation and statistical learning for multicriteria decision support: A review (Q621964) (← links)
- Mathematical optimization in classification and regression trees (Q828748) (← links)
- Inferring descriptive and approximate fuzzy rules for credit scoring using evolutionary algorithms (Q856247) (← links)
- A note on knowledge discovery using neural networks and its application to credit card screening (Q948676) (← links)
- Confidence intervals for probabilistic network classifiers (Q957276) (← links)
- Credit scoring for profitability objectives (Q1039802) (← links)
- A reference model for customer-centric data mining with support vector machines (Q1042173) (← links)
- Induction over constrained strategic agents (Q1046077) (← links)
- High dimensional data classification and feature selection using support vector machines (Q1681156) (← links)
- An analytic hierarchy model for classification algorithms selection in credit risk analysis (Q1718069) (← links)
- Investment decisions and sensitivity analysis: NPV-consistency of rates of return (Q1754333) (← links)
- Predicting loss severities for residential mortgage loans: a three-step selection approach (Q1754749) (← links)
- Greedy rule generation from discrete data and its use in neural network rule extraction (Q1932069) (← links)
- Fuzzy factorization machine (Q2055588) (← links)
- Credit default prediction from user-generated text in peer-to-peer lending using deep learning (Q2140350) (← links)
- Risk analysis via Łukasiewicz logic (Q2156531) (← links)
- Instance-dependent cost-sensitive learning for detecting transfer fraud (Q2242220) (← links)
- Optimal market-making strategies under synchronised order arrivals with deep neural networks (Q2246653) (← links)
- Sparsity in optimal randomized classification trees (Q2301963) (← links)
- Classification with incomplete survey data: a Hopfield neural network approach (Q2387274) (← links)
- Financial system modeling using deep neural networks (DNNs) for effective risk assessment and prediction (Q2416723) (← links)
- Heuristic approaches for support vector machines with the ramp loss (Q2448185) (← links)
- Bayesian kernel based classification for financial distress detection (Q2488920) (← links)
- Comprehensible credit scoring models using rule extraction from support vector machines (Q2643977) (← links)
- Optimal randomized classification trees (Q2668720) (← links)
- On sparse optimal regression trees (Q2670540) (← links)
- Extração de regras de classificação a partir de redes neurais para auxílio à tomada de decisão na concessão de crédito bancário (Q3621492) (← links)
- EFFECT OF THE COMPANY RELATIONSHIP NETWORK ON DEFAULT PREDICTION: EVIDENCE FROM CHINESE LISTED COMPANIES (Q5048583) (← links)
- Deep learning for limit order books (Q5234311) (← links)
- On mathematical optimization for clustering categories in contingency tables (Q6106171) (← links)
- The attribution matrix and the joint use of finite change sensitivity index and residual income for value-based performance measurement (Q6106508) (← links)
- On clustering and interpreting with rules by means of mathematical optimization (Q6109555) (← links)
- Explainable AI for operational research: a defining framework, methods, applications, and a research agenda (Q6572853) (← links)
- Hybridized artificial neural network classifiers with a novel feature selection procedure based genetic algorithms and information complexity in credit scoring (Q6579526) (← links)
