Jhang, "Clustering-based undersampling in class-imbalanced data," Information Sciences, vol. 409, pp. 17-26, 2017.W.-C. Lin, C.-F. Tsai, Y.-H. Hu, and J.-S. Jhang, "Clustering- based undersampling in class-imbalanced data," Information Sciences, vol. 409-410, pp. 17-26, ...
Fig.1 An illustration of k means clustering based under- sampling algorithm 74 第8 期 110个单个演员的动作文件,涉及到每个演员3耀10 s之 间的每个动作。使用描述系统,能够创造出各种不同条 件下的动态响应。图2显示了一个这样的响应,从一个
For example, by keeping the sparsity constraint strict enough, a model based on a few parameters can be formed, exhibiting less overfitting. In the case of noise and outliers, it has been shown that under certain conditions, it is highly probable that sparse and redundant representations admit ...
Clustering-based undersampling in class-imbalanced data - ScienceDirect Class imbalance is often a problem in various real-world data sets, where one class (i.e. the minority class) contains a small number of data points and th... Wei-Chao,Lin,Chih-Fong,... - 《Information Sciences》 被...
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In addition, since Xr−1 is closer to the true cluster center μk, it is located in a denser region under the true probability distribution and is more likely to have a lower label acceptance threshold relative to Xr+1. Therefore, Xr−1 is more likely to receive a label from Xr com...
This type of clustering-based analysis tool is currently lacking in both the scientific literature and healthcare practices. Most community detection methods lack a proper way to control the size of the clusters, which often tend to become too large for manual investigation. This is a serious def...
Other methods falling under this category include Knorr’s unified approach22. A limitation of distance-based methods is their susceptibility to the curse of dimensionality problem. The number of parameters in these models grows quadratically with the number of dimensions, rendering them less suitable...
To improve the lack and stochasticity of gene expression information in single-cell experiments, several in silico gene imputation methods have been designed based on different principles. Gene imputation infers gene expression in a given cell type or state, based on the information from other biologi...
i.e., the difference between the logarithm of the normalized sum Wk of pairwise distances in the k clusters and its expectation under a null reference distribution generated by Monte Carlo sampling. The gap statistic analysis was independently performed for each transformation applied to the data ...