We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables.
This menu includes all the advanced algorithms and search capabilities that can be applied on the database, such as diversity selection, creation of new DRCS models, similarity search, etc.
It is worth noting that quality score may be affected by the order the subject uses the scanners, and other image quality algorithms can also be applied on the database.
Rank-Sort-MDP(_{mathrm {REF}}) relies on the output of MDP(_{mathrm {REF}}) algorithm which is successfully tested, and evaluated, and applied on different databases bigger than actual one.
The feature subset selection methods are applied on both databases (VAM, EMO-DB).
Such information could be obtained from factor analyses applied on large databases, observational studies and large long-term therapeutic trials: this type of analyses appears capable of identifying patients and treatments subtypes and analysing their relationship.
The methodology was applied on a university database.
Furthermore, the results are almost identical to those of another pilot study where a different statistical methodology was applied on the same database.
The proposed approach has also been applied on the ORL database [24], which contains 10 different images of each of the 40 distinct individuals.
Later on, the discriminant model was applied on a huge database so that fourteen compounds were selected as potential new hypoglycaemics.
