TreeKDE: clustering multivariate data based on decision tree and using one-dimensional kernel density estimation
From MaRDI portal
Publication:6547179
DOI10.1080/02664763.2022.2159339MaRDI QIDQ6547179
D. Scaldelai, Luiz Carlos Matioli, Sandrina Rafaela Andrade Santos
Publication date: 30 May 2024
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An advancement in clustering via nonparametric density estimation
- Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
- A complete gradient clustering algorithm formed with kernel estimators
- Finding Groups in Data
- An efficient algorithm for a complete link method
- Nonparametric Kernel Density Estimation and Its Computational Aspects
- A new algorithm for clustering based on kernel density estimation
- Dynamic Tensor Clustering
- Essential Tensor Learning for Multi-View Spectral Clustering
- Multivariate Density Estimation
- MulticlusterKDE: a new algorithm for clustering based on multivariate kernel density estimation
- The Elements of Statistical Learning
This page was built for publication: TreeKDE: clustering multivariate data based on decision tree and using one-dimensional kernel density estimation