However, the experiments show as well that the use of the algorithm cannot be recommended for domains which require a very specific concept description.doi:http://dx.doi.org/Johannes FurnkranzFürnkranz, J. and
The normal parameters were a burden, as they were not used anywhere in the algorithm.In this project, apart from removing these 3, unused normal parameters, we introduce these 3 changes:Multiple Point CloudsWith our SH culling technique we end up with sets of primitives that have a different...
If the height of the saplings absent from the previous year’s data was less than 400 cm, the algorithm categorized them as “no longer within our observation scope” (potentially due to mortality). Conversely, if the saplings’ height exceeded 400 cm, they were considered as potentially ...
Any volume change induced by normalization was adjusted via a modulation algorithm. Spatially normalized GM images were smoothed by a Gaussian kernel of 8 mm full width at half maximum. Regional differences in GM volume between groups were analyzed in SPM 12 using two-sample t-test models. ...
tectatthereceiver.Maximumlikelihood(ML)algorithm providesthebestperformance,butitisanNP-hardprob- lem.Thelinearalgorithm,suchasthezeroforcing(ZF) andtheminimummeansquareerror(MMSE),haslow calculationcomplexity,buttheperformanceisoftentoo badtobeused.Thesuccessiveinterferencecancellation (SIC)andorderedSIC(OSIC)...
Type 2 diabetes was defined using a modified version of the Electronic Medical Records and Genomics (eMERGE) Network type 2 diabetes electronic phenotyping algorithm32. In brief, patients were considered to have type 2 diabetes if they had at least two out of (1) a diagnosis of type 2 diabet...
Fumkranz J,Widmer G.Incremental reduced errorpruning.Machine Learning: Proceedings ofthe Eleventh Annual Conference. 1994Furnkranz J, Widmer G. Incremental reduced error pruning. Proceedings of the Eleventh International Conference of Machine Learning; 1994; New Brunswick, New Jersey: Morgan Kaufmann; ...
Because of this intractability result, we have to consider approximating reduced error pruning. Unfortunately, it turns out that even finding an approximate solution of arbitrary accuracy is computationally infeasible. In particular, reduced error pruning of branching programs is APX-hard. Our experiments...
IMPROVED APPROACH AND IMPLEMENTATION FOR DECISION TREE CLASSIFICATION USING REDUCED ERROR PRUNINGDecision trees are one of the most profound researched domains in Knowledge Discovery. Regardless of such advantages as the ability to explain the choice procedure and low computational costs, decision trees ...
In this paper, we prove under a plausible complexity hypothesis that Reduced Error Pruning of branching programs is hard to approximate within log 1 δ n, for every δ>0, where n is the number of description variables, a measure of the problem's complexity. The result holds under the ...