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ClusteringOptions Class Reference |
Options object for hierarchical clustering. More...
#include <vigra/hierarchical_clustering.hxx>
Public Member Functions | |
ClusteringOptions & | maxMergeDistance (double val) |
ClusteringOptions & | minRegionCount (size_t count) |
ClusteringOptions & | nodeFeatureImportance (double val) |
ClusteringOptions & | nodeFeatureMetric (metrics::MetricType metric) |
ClusteringOptions & | sizeImportance (double val) |
ClusteringOptions & | verbose (bool val=true) |
Options object for hierarchical clustering.
#include <vigra/hierarchical_clustering.hxx>
Namespace: vigra
This class allows to set various parameters of hierarchicalClustering(). See there for usage examples.
ClusteringOptions& minRegionCount | ( | size_t | count | ) |
Stop merging when the number of clusters reaches this threshold.
Default: 1 (don't stop early)
ClusteringOptions& maxMergeDistance | ( | double | val | ) |
Stop merging when the weight of the cheapest edge exceeds this threshold.
Default: infinity (don't stop early)
ClusteringOptions& nodeFeatureImportance | ( | double | val | ) |
Importance of node features relative to edge weights.
Must be between 0 and 1, with 0 meaning that node features are ignored, and 1 meaning that edge weights are ignored.
Default: 0.5 (equal importance)
ClusteringOptions& sizeImportance | ( | double | val | ) |
Importance of node size.
Must be between 0 and 1, with 0 meaning that size is ignored, and 1 meaning that the algorithm prefers to keep cluster sizes balanced.
Default: 1.0 (prefer like-sized clusters)
ClusteringOptions& nodeFeatureMetric | ( | metrics::MetricType | metric | ) |
Metric to be used when transforming node features into cluster distances.
The cluster (= node) distance is the respective norm of the difference vector between the corresponding node feature vectors.
Default: metrics::ManhattanMetric (L1-norm of the feature difference)
ClusteringOptions& verbose | ( | bool | val = true | ) |
Display progress information.
Default: false
© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) |
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