In this paper, we introduce the algorithm ClicoT (CLustering mixed-type data Including COncept Trees) as reported by Behzadi et al. (Advances in Knowledge Discovery and Data Mining, Springer, Cham, 2019) which is based on the minimum description length principle. Profiting of the conceptual ...
Since clusters are used for predictive purposes, a clustering algorithm which takes as input the number K of clusters would affect the predictive capabilities of the learned models. In particular, setting K equal to the number of classes would lead to identifying models which are too general and...
Cell type annotation can resolve cellular heterogeneity across tissues, developmental stages and organisms, and improve our understanding of cellular and gene functions in health and disease. Many unsupervised scRNA-seq clustering methods have been proposed2,3,4, which are followed by time-consuming ...
A number of clustering methods have been developed by using scRNA-seq data; e.g., Xu and Su designed a new method by using a shared nearest neighbor approach followed by a quasi-clique-based clustering algorithm (SNN-cliq) to cluster single-cell transcriptomes [14]. In addition, the approa...
D2 clustering algorithm. Examining global effects of identified variants on complex phenotypes To verify that Huatuo enables identifications of the genetic regulation that serves as potential functional mechanisms underlying the GWAS associations of complex diseases and traits, we constructed logistic ...
To address this difficulty, in this paper a two-stage clustering algorithm for multi-type relational data (TSMRC) has been proposed Based on the analysis of data and relationships, TSMRC has two stages, which are benefit to improve the efficiency of clustering. To improve the quality of ...
Experimental results on Movie database show the effectiveness of this method.GAO YingLIU DaYouQI HongLIU He高滢刘大有齐红刘赫软件学报GAO Ying,LIU Da-You,QI Hong,LIU He."Semi-Supervised K-Means ClusteringAlgorithm for Multi-Type Relational Data". Journal of Software . 2008...
The method using fuzzy C-mean clustering algorithm and the back-propagation technique to determine parameters of type-2 TSK fuzzy classifier was presented. The generalized bell primary membership function was used to examine the performance of the classifier with different shapes of membership functions...
one attempts to determine the best transformation for aligning similar images. Such problems typically require minimizing a dissimilarity measure with multiple local minima. We describe a global optimization algorithm and apply it to the problem of identifying the best transformation for aligning two image...
8a). However, they lack the expression of key peripheral myelin constituent genes such as MPZ and PMP2, confirming the absence of actual myelin in the lamprey PNS28. Together with the co-clustering of this cell type with mouse satellite glia and Schwann cells (Fig. 2c), our observations ...