Assessing variable importance in clustering: a new method based on unsupervised binary decision trees.
Badih GhattasPierre MichelLaurent BoyerPublished in: Comput. Stat. (2019)
Keyphrases
- clustering method
- significant improvement
- detection method
- decision trees
- unsupervised learning
- k means
- probabilistic model
- dynamic programming
- hierarchical clustering
- decision rules
- support vector machine
- pairwise
- unsupervised clustering
- objective function
- unsupervised manner
- unsupervised classification
- neural network
- spectral clustering
- distance metric
- data sets
- cluster validation
- segmentation method
- computational cost
- cost function
- training set
- computational complexity
- similarity measure
- learning algorithm
- machine learning