Statements (28)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:data_visualization_method
gptkb:statistical_technique |
| gptkbp:alternativeName |
gptkb:MDS
|
| gptkbp:canBe |
gptkb:Metric
non-metric |
| gptkbp:foundIn |
configuration of points
|
| gptkbp:input |
distance matrix
|
| gptkbp:introducedIn |
1950s
|
| gptkbp:output |
low-dimensional representation
|
| gptkbp:outputDimension |
usually 2 or 3
|
| gptkbp:preserves |
pairwise distances
|
| gptkbp:reduces |
stress function
|
| gptkbp:relatedTo |
gptkb:t-SNE
Principal Component Analysis Classical Multidimensional Scaling Non-metric Multidimensional Scaling Sammon mapping |
| gptkbp:requires |
dissimilarity data
|
| gptkbp:supportsAlgorithm |
unsupervised learning
|
| gptkbp:usedFor |
visualizing similarity or dissimilarity data
|
| gptkbp:usedIn |
ecology
marketing psychology bioinformatics |
| gptkbp:visualizes |
high-dimensional data
|
| gptkbp:bfsParent |
gptkb:t-distributed_Stochastic_Neighbor_Embedding
|
| gptkbp:bfsLayer |
7
|
| https://www.w3.org/2000/01/rdf-schema#label |
Multidimensional Scaling
|