51 results on '"Altman N"'
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2. Comparing classifier performance with baselines.
3. Errors in predictor variables.
4. Convolutional neural networks.
5. Neural networks primer.
6. Regression modeling of time-to-event data with censoring.
7. Survival analysis-time-to-event data and censoring.
8. The class imbalance problem.
9. Author Correction: Graphical assessment of tests and classifiers.
10. Graphical assessment of tests and classifiers.
11. Author Correction: The SEIRS model for infectious disease dynamics.
12. Testing for rare conditions.
13. The standardization fallacy.
14. Author Correction: Nested designs.
15. Uncertainty and the management of epidemics.
16. The SEIRS model for infectious disease dynamics.
17. Modeling infectious epidemics.
18. Markov models - training and evaluation of hidden Markov models.
19. Markov models - hidden Markov models.
20. Markov models-Markov chains.
21. Quantile regression.
22. Author Correction: Two-level factorial experiments.
23. Analyzing outliers: robust methods to the rescue.
24. Two-level factorial experiments.
25. Predicting with confidence and tolerance.
26. Optimal experimental design.
27. The curse(s) of dimensionality.
28. Statistics versus machine learning.
29. Machine learning: supervised methods.
30. Points of Significance: Machine learning: a primer.
31. Analyzing outliers: influential or nuisance?
32. Multiple linear regression.
33. Simple linear regression.
34. Association, correlation and causation.
35. Points of Significance. Bayesian networks.
36. Sampling distributions and the bootstrap.
37. POINTS OF SIGNIFICANCE: Bayesian statistics.
38. Points of significance: Bayes' theorem.
39. Split plot design.
40. Points of significance: Sources of variation.
41. Points of significance: two-factor designs.
42. Points of significance: nested designs. For studies with hierarchical noise sources, use a nested analysis of variance approach.
43. Points of significance: replication.
44. Points of significance: Analysis of variance and blocking.
45. Points of view: designing comparative experiments.
46. Points of significance: Nonparametric tests.
47. Points of significance: Comparing samples—part I.
48. Visualizing samples with box plots.
49. Significance, P values and t-tests.
50. Points of significance: error bars.
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