Despite pension fund managers being largely unconstrained in their investment decisions, this paper reports evidence of clustering in the performance of a large cross-section of UK pension fund managers around
Although less straightforward, the performance evaluation on an unsupervised learning model is also important. In this post, I’m going to talk about how to evaluate the performance of a clustering model, a major task in unsupervised learning, if the ground-truth labels are not available. So, ...
i.e., the Manhattan distance, the Euclidean distance and the Cosine distance. The results are presented in Table6, with the best results marked in boldface. As can be seen, AEEA always obtains the best clustering performance when the cosine distance is adopted. This indicates that the cosine ...
We first assessed GraphST’s spatial clustering performance on the LIBD human dorsolateral prefrontal cortex (DLPFC) dataset36. This dataset contains spatially resolved transcriptomic profiles of 12 DLPFC slices, each depicting the four or six layers of the human dorsolateral prefrontal cortex and white...
Our first task is to find out the performance of 28 different distance measures to predict the sample-based confidence scores for t-SNE embeddings. The distance measures are presented in Table 1. In accordance with8, we trained an RF regressor on the training sets of the AMB18 and Baron Hu...
Our systematic evaluation of clustering performance in these five datasets demonstrates that there is no existing clustering method that universally performs best across all datasets. We propose a combined metric of BC and UU that capitalizes on the complementary strengths of the two metrics. Video ...
Therefore, in order to improve the clustering performance, in addition to improving the local density estimation techniques, designing an adequate distance measure has increasingly become the Comparison with several improved DPCs with various local densities In order to demonstrate the effectiveness of the...
《Performance guarantees for hierarchical clustering》论文:http://cseweb.ucsd.edu/~dasgupta/papers/hier-jcss.pdfGitHub:https://github.com/jonfink/hcluster Abstract 作者表示,对于任何度量空间中的任何数据集,都可以构建一个层次聚类,保证对于每个k,产生的k聚类的cost最多是最优k聚类的8倍。 这里,聚类的co...
p= self.target_distribution(q)#update the auxiliary target distribution p#evaluate the clustering performancey_pred = q.argmax(1)ifyisnotNone: acc= np.round(metrics.acc(y, y_pred), 5) nmi= np.round(metrics.nmi(y, y_pred), 5) ...
1 Investment performance by institutions outside the US has been much less intensively researched. This omission is important, since differences in institutional and legal frameworks and, indeed, different investment cultures and fund manager compensation schemes might help to shed additional light on ...