Pages that link to "Item:Q1429953"
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The following pages link to Evaluating feature selection methods for learning in data mining applications. (Q1429953):
Displaying 17 items.
- Feature selection for support vector machines using generalized Benders decomposition (Q319318) (← links)
- Integer programming models for feature selection: new extensions and a randomized solution algorithm (Q322475) (← links)
- Multicriteria variable selection for classification of production batches (Q439462) (← links)
- Iconic and multi-stroke gesture recognition (Q733088) (← links)
- A fast heuristic attribute reduction approach to ordered decision systems (Q1681488) (← links)
- Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods (Q1926754) (← links)
- Optimization problems for machine learning: a survey (Q2029894) (← links)
- Fuzzy similarity and entropy (FSAE) feature selection revisited by using intra-class entropy and a normalized scaling factor (Q2100516) (← links)
- Regression with adaptive Lasso and correlation based penalty (Q2109879) (← links)
- Optimal Boolean lattice-based algorithms for the U-curve optimization problem (Q2200667) (← links)
- The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing (Q2497261) (← links)
- A mixed integer linear programming support vector machine for cost-effective group feature selection: branch-cut-and-price approach (Q2670542) (← links)
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- A novel feature selection approach based on clustering algorithm (Q5033944) (← links)
- Supervised feature compression based on counterfactual analysis (Q6572856) (← links)
- Financial distress prediction using support vector machines and logistic regression (Q6637763) (← links)
