A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.
Martin EsterHans-Peter KriegelJörg SanderXiaowei XuPublished in: KDD (1996)
Keyphrases
- detection algorithm
- learning algorithm
- density based clustering
- k means
- clustering method
- optimal solution
- segmentation algorithm
- hierarchical clustering
- convergence rate
- noisy data
- data clustering
- optimization algorithm
- dynamic programming
- np hard
- subspace clustering
- synthetic datasets
- similarity measure
- recognition algorithm
- search space
- data sets
- preprocessing
- high accuracy
- input data
- computational complexity
- clustering algorithm
- high efficiency
- signal to noise ratio
- initial set
- probabilistic model
- worst case
- computational cost
- cost function
- significant improvement
- evolutionary algorithm
- lower bound
- search algorithm
- objective function
- neural network