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Author Brazdil, Pavel
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data Transformation ♦ Model Selection ♦ Possible Candidate ♦ Algorithm Lead ♦ Uncorrelated Error ♦ Various Proposal ♦ Confidence Level ♦ Certain Criterion
Abstract n confidence level, the approach does indeed identify the best possible candidate and errs as expected. The disadvantage of this approach is that it is time consuming, due to the fact that it is necessary to evaluate all algorithms, some of which can be quite slow. Various proposals have been presented how to speed up this process. One possibility is to pre-select some algorithms using certain criteria and then limit the experimentation to this subset. Some people have suggested that we should preferably use algorithms which behave rather differently form one another. One criteria for deciding this is by examining whether the algorithms lead to uncorrelated errors (Ali and Pazzani, 1996). Another possibility is to try to reduce the number of cycles of cross-validation without effecting the reliability of the result. Moore and Lee (1994) have proposed a technique referred to as racing, which permits to terminate the evaluation of those algorithms which appear to
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 1998-01-01