While the term 'appropriate' is usually subjective and largely dependent upon the domain that one is talking about, I am here asking whether the exclusion of outliers goes against the principle of ensemble learning.
For instance, in an information retireval system that combines multiple weak learners in the hope of producing an overall good result, would it be considered inappropriate in an academic setting for outliers, that do not have statistical significance, to be excluded from each of the learners prior to combination? Or, to put it another way, would the exclusion of outliers at each step of an ensemble process defeat some of the purpose of an ensemble method?
The importance of this decision lies in the weighting that would be applied to the different learners. A learner with a high occurrence of outliers will be negatively effected in terms of its weighting.