36 results on '"Johansson, U."'
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2. Genetic programming - a tool for flexible rule extraction
3. Building Neural Network Ensembles using Genetic Programming
4. Locally induced predictive models.
5. One tree to explain them all.
6. Evolving accurate and comprehensible classification rules.
7. Pin-pointing concept descriptions.
8. Comparing methods for generating diverse ensembles of artificial neural networks.
9. Improving GP classification performance by injection of decision trees.
10. Ensemble member selection using multi-objective optimization.
11. Evolving decision trees using oracle guides.
12. Using genetic programming to obtain implicit diversity.
13. The problem with ranking ensembles based on training or validation performance.
14. G-REX: A Versatile Framework for Evolutionary Data Mining.
15. Increasing rule extraction accuracy by post-processing GP trees.
16. Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes.
17. On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers.
18. Concept Description - A Fresh Look.
19. Inconsistency - Friend or Foe.
20. The Importance of Diversity in Neural Network Ensembles - An Empirical Investigation.
21. Empirically investigating the importance of diversity.
22. Benefits of relating the Retail Domain and Information Fusion.
23. Obtaining Accurate Neural Network Ensembles.
24. Increased performance with neural nets - an example from the marketing domain.
25. A study on active flutter detection and control.
26. A general time-discrete equivalent to a time-continuous Gaussian channel (Corresp.).
27. High-Capacity Digital Line Links.
28. Increased performance with neural nets - an example from the marketing domain
29. Building Neural Network Ensembles using Genetic Programming
30. Predicting the impact of advertising: a neural network approach
31. A study on active flutter detection and control
32. Neural networks mine for gold at the greyhound racetrack
33. Automatically balancing accuracy and comprehensibility in predictive modeling.
34. Neural networks and rule extraction for prediction and explanation in the marketing domain.
35. Neural networks mine for gold at the greyhound racetrack.
36. Predicting the impact of advertising: a neural network approach.
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