Multi-label classification is one of the important research areas in data mining. In this paper, a new multilabel classification method using multinomial naive Bayes is proposed. We use a new fine-grained weighting method for calculating the weights of feature values in multinomial naive Bayes. Our experiments show that the value weighting method could improve the performance of multinomial nai...

OBJECTIVE Methods exist to appropriately perform association analyses in pedigrees. However, for genome-wide association analysis, these methods are computationally impractical. It is therefore important to determine alternate methods that can be efficiently used genome-wide. Here, we introduce a new algorithm that considers all relationships simultaneously in arbitrary-structured pedigrees and...

In this paper, we propose a new depth map upsampling method to increase the depth image resolution using edge information. Although the joint bilateral upsampling (JBU) method expands the resolution of the depth map using two weighting functions, the complexity of JBU is relatively high. In the proposed upsampling method, we reduce the complexity of depth map upsmapling operation using a color ...

In this paper, a watermark embedding method, using amplitude modulation technique, based on Gaussian pixel-weighting marks was proposed. The method utilized a technique of weighting marks by averaging the luminance of its own pixel and its neighboring pixels, and used it as an additional scaling factor in the existing watermark embedding methods, The watermark retrieval process was borrowed fro...

The convergence of the restarted GMRES method can be significantly improved, for some problems, by using a weighted inner product that changes at each restart. How does this weighting affect convergence, and when is it useful? We show that weighted inner products can help in two distinct ways: when the coefficient matrix has localized eigenvectors, weighting can allow restarted GMRES to focus o...

Based on fuzzy set theory, this paper proposes a novel weighting method for spatial adaptive patch-based image denoising algorithm which can be considered as an extension of nonlocal means filtering. First, a fuzzy clustering algorithm for weighting data points is applied to reduce the estimate bias which arises from the unrelated points. The weighting function is determined by optimal fuzzy pa...