arXiv Machine Learning By Davide Chicco, Nicoletta Benvenuto

An unsupervised clustering analysis of breast cancer data derived from electronic health records enhanced through UMAP dimensionality reduction

Read the original on arXiv Machine Learning →

arXiv:2607. 19089v1 Announce Type: new Abstract: Breast cancer is one of the most widespread types of cancer, affecting approximately 8 million women worldwide.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jun 30

Interpretable Clustering: A Survey

arXiv:2409. 00743v4 Announce Type: replace-cross Abstract: In recent years, much of the research on clustering algorithms has primarily focused on enhancing their accuracy and efficiency, frequently at the expense of interpretability.

By Lianyu Hu, Mudi Jiang, Junjie Dong, Xinying Liu, Zengyou He