Quantitative cluster evaluation metrics on t-SNE feature embeddings for different models. Higher Silhouette and Calinski–Harabasz scores indicate better class separation, while lower Davies–Bouldin values denote tighter intra-class clustering.
收藏Figshare2025-11-07 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Quantitative_cluster_evaluation_metrics_on_t-SNE_feature_embeddings_for_different_models_Higher_Silhouette_and_Calinski_Harabasz_scores_indicate_better_class_separation_while_lower_Davies_Bouldin_values_denote_tighter_intra-class_clustering/30567707
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Quantitative cluster evaluation metrics on t-SNE feature embeddings for different models. Higher Silhouette and Calinski–Harabasz scores indicate better class separation, while lower Davies–Bouldin values denote tighter intra-class clustering.
创建时间：
2025-11-07
