Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
In this paper we propose a hybrid FPGA using nanoscale clusters with an architecture similar to clusters of traditional CMOS FPGAs. The proposed cluster is made of a crossbar of n...
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
Correlations between prototypical usability metrics from 90 distinct usability tests were strong when measured at the task-level (r between .44 and .60). Using test-level satisfac...
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improve...