The proposed first stage has complementary characteristics to the shortcoming of Nearest-better Clustering (NBC). We introduce a weighted gradient and distance-based clustering method (WGraD) and two methods for
Here we employ the nearest-better clustering basin identification method derived in a previous chapter for setting up two niching evolutionary algorithms. After doing parameter testing, we investigate how these algorithms perform in comparison to other recent methods for the all-global and one-global ...
Keywords: elephants; elephant recognition; object recognition; image segmentation; K-nearest neighbour; k-means clustering; shape features; feature extraction; KNN classifier.DOI: 10.1504/IJESDF.2015.070390International Journal of Electronic Security and Digital Forensics, 2015 Vol.7 No.3, pp.234 - ...
Preuss, M.: Niching the cma-es via nearest-better clustering. In: Proceedings of the 12th Annual Conference Companion on Genetic and Evolutionary Computation, GECCO 2010, pp. 1711–1718. ACM (2010)M. Preuss, Niching the CMA-ES via nearest-better clustering, in: Proceedings of the 12th ...
Here we first collect the most important objectives for a basin identification (and thereby clustering) algorithm in the optimization context and then propose a technique for detecting clusters in populations of search points that correspond to basins of attraction. We present this method early and ...
Here we employ the nearest-better clustering basin identification method derived in a previous chapter for setting up two niching evolutionary algorithms. After doing parameter testing, we investigate how these algorithms perform in comparison to other recent methods for the all-global and one-global ...
ClusteringClassification time and space requirements of nearest neigh bor based classifiers depends directly on the training set size. There exist several ways to reduce the training set size, and also there exist some methods to generate artificial training sets which are aimed at achievi ng better...