Feature-guided clustering of multi-dimensional flow cytometry datasets.
Qing T. ZengJuan Pablo PrattJane PakDino RavnicHarold HussSteven J. MentzerPublished in: J. Biomed. Informatics (2007)
Keyphrases
- multi dimensional
- clustering algorithm
- synthetic datasets
- multi dimensional data
- synthetic and real datasets
- k means
- categorical data
- data mining tasks
- high dimensional datasets
- clustering approaches
- cluster analysis
- image features
- unsupervised learning
- benchmark datasets
- feature importance
- flow cytometry
- spectral clustering
- multiple dimensions
- clinical setting
- pattern recognition
- decision making
- data clustering
- hierarchical clustering
- information theoretic
- data cube
- sequential patterns
- real time
- distance metric
- outlier detection
- self organizing maps
- high dimensional data
- data points
- feature vectors
- image processing
- data sets