In this paper, we propose lazy bagging (LB), which builds bootstrap replicate bags based on the characteristics of test instances. Upon receiving a test instance xk, LB trims bootstrap bags by taking into consideration xk’s nearest neighbors in the training data. Our hypothesis is that an unlabeled instance’s nearest neighbors provide valuable information to enhance local learning and generate ...

We have applied tests for detecting recombination to genes of foot-and-mouth disease virus (FMDV). Our approach estimated summary statistics of linkage disequilibrium (LD), which are sensitive to recombination. Using the genealogical relationships, rate heterogeneity and mutation parameters estimated from individual sets of aligned gene sequences, we simulated matching RNA sequence datasets wit...

it is very important to study and simulate s-wave structure for near surface (alluvium parts, in particular) owing to its direct relationship to urban facilities in geotechnical and earthquake engineering studies. so, in seismic microzonation, the first step is to study and identify s-wave pattern in alluvium in order to categorize different parts of cites according to s-wave velocity. current ...

Several algorithms exist to address the issues concerning parameter reduction of soft sets. The most recent concept of Normal Parameter Reduction (NPR) is introduced, which overcomes the problem of suboptimal choice and added parameter set of soft sets. However, the algorithm involves a great amount of computation. In this thesis, a New Efficient Normal Parameter Reduction algorithm (NENPR) of ...

We propose a locally adaptive technique to address the problem of setting the bandwidth parameters optimally for kernel density estimation. Our technique is eecient and can be performed in only two dataset passes. We also show how to apply our technique to eeciently solve range query approximation, classiication and clustering problems for very large datasets. We validate the eeciency and accur...