Pages that link to "Item:Q1779549"
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The following pages link to Cost-sensitive learning and decision making revisited (Q1779549):
Displaying 15 items.
- Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research (Q319944) (← links)
- Cost-sensitive boosting algorithms: do we really need them? (Q331693) (← links)
- Modeling churn using customer lifetime value (Q1011323) (← links)
- A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning (Q1015231) (← links)
- Cost-sensitive learning based on Bregman divergences (Q1959517) (← links)
- Finding a short and accurate decision rule in disjunctive normal form by exhaustive search (Q1959589) (← links)
- Machine learning for credit scoring: improving logistic regression with non-linear decision-tree effects (Q2060438) (← links)
- Cost-sensitive business failure prediction when misclassification costs are uncertain: a heterogeneous ensemble selection approach (Q2183867) (← links)
- Using POMDPs for learning cost sensitive decision trees (Q2238662) (← links)
- Cost-sensitive feature selection of numeric data with measurement errors (Q2375660) (← links)
- A hierarchical model for test-cost-sensitive decision systems (Q2390365) (← links)
- A survey of cost-sensitive decision tree induction algorithms (Q2875106) (← links)
- Maximum likelihood in cost-sensitive learning: model specification, approximations, and upper bounds (Q2896188) (← links)
- Cost allocation with learning and forgetting considerations in a monopolistically competitive market (Q3063822) (← links)
- Cost-sensitive learning and decision making for massachusetts pip claim fraud data (Q3156795) (← links)
