The ability to predict the quality of a software object can be viewed as a classification problem, where software metrics are the features and expert quality rankings the class lab...
Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale an...
The growing use of digital signal processors (DSPs) in embedded systems necessitates the use of optimizing compilers supporting special hardware features. Due to the irregular arc...
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
A major challenge for genomewide disease association studies is the high cost of genotyping large number of single nucleotide polymorphisms (SNP). The correlations between SNPs, h...