View source for Talk:Ensemble learning

== Reviewer A:  ==

I have several suggestions:

1. Several spelling and grammar mistakes remain, some of which do affect the ability to interpret the article.

2. "Nor an improvement on the ensemble’s average performance can only be guaranteed for certain special cases (Fumera 2005)." I think you mean to say that the improvement can be guaranteed in some special cases.

3. Boosting section, near the end. The fact that the boosted ensemble's training error is less than the upper bound epsilon does not mean that it outperforms the best individual base model. In fact, it outperforms the worst individual base model.

4. In AdaBoost algorithm, equation 4, don't have both expressions for the error. They are redundant.

5. Mixtures of Experts is not normally trained with bootstrapping. Also, the mixture of experts does not really use a meta-classifier. MOE uses the errors of the outputs of the base models to train the gating network, but does not train on the outputs themselves the way stacking does. I suggest a separate diagram.

6. Under voting methods, note that having an odd number of classifiers does not help avoid ties unless the number of classes is 2. Even for an even number of classes, if the number of classes is greater than the number of base classifiers, then having an odd number of classifiers does not help. I would just remove the conditions on odd number of classifiers, or just make clear for that first part that you are dealing with the two-class case.