A data selection framework for k-means algorithm to mine high precision clusters.
Zhengzheng LouChaoyang ZhangPublished in: ICNC-FSKD (2017)
Keyphrases
- k means
- high precision
- clustering algorithm
- cluster centers
- input data
- hierarchical clustering
- data clustering
- clustering result
- cluster structure
- hierarchical clustering algorithm
- data sets
- cluster analysis
- noisy data
- clustering method
- data points
- high accuracy
- spectral clustering
- clustering framework
- fuzzy k means
- learning algorithm
- data analysis
- synthetic datasets
- clustering analysis
- selection algorithm
- expectation maximization
- dissimilarity matrix
- data sources
- clustering quality
- probabilistic model
- hierarchical clustering algorithms
- high recall
- pairwise
- objective function
- data samples
- data mining techniques
- self organizing maps
- fuzzy clustering algorithm
- data objects
- center based clustering
- valued data
- clustering approaches
- unsupervised clustering
- similarity matrix
- fuzzy c means
- high dimensional data