MaxD K-Means: A Clustering Algorithm for Auto-generation of Centroids and Distance of Data Points in Clusters.
Wan Maseri Binti Wan MohdAbul Hashem BegTutut HerawanKhandakar Fazley RabbiPublished in: ISICA (2012)
Keyphrases
- k means
- clustering algorithm
- data points
- cluster centers
- cluster centroids
- euclidean distance
- distance function
- data clustering
- distance metric
- fuzzy c means
- cluster analysis
- clustering quality
- meaningful clusters
- sufficient statistics
- cluster structure
- unsupervised clustering
- fuzzy k means
- document clustering
- overlapping clusters
- nearest neighbor
- dimensionality reduction
- clustering approaches
- hierarchical clustering
- clustering method
- expectation maximization
- fuzzy clustering
- text clustering
- self organizing maps
- spectral clustering
- clustering analysis
- clustering solutions
- high dimensional
- feature space
- agglomerative hierarchical clustering
- hierarchical clustering algorithms
- graph clustering
- data distribution
- high dimensional data
- hierarchical clustering algorithm
- cluster labels
- input data
- initial cluster centers
- clusters of arbitrary shapes
- affinity propagation
- agglomerative clustering
- clustering framework
- distance measure
- squared euclidean distance