摘要(英) |
For clustering methods, the γ-SUP algorithm possesses several favorable proper-
ties, making it a valuable tool in clustering. However, its original intention was merely
to cluster images with high similarity, without providing a confidence interval for each
cluster. It implies that the γ-SUP algorithm lacks evaluation for uncertainty from a sample. In this article, we provide a confidence interval and apply this method to NBA data.
Based on the γ-SUP algorithm, confidence intervals for clusters of NBA players are established to understand distinctive features between groups. In other words, we want to identify standout abilities or the needs of each player, which can provide managementdecisions in a free agent market. |
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