KmeansClustering3 Node
KmeansClustering2 node groups the data into clusters based on the values of the three input features.
Category
Terrain Features/Clustering
Inputs
| Name | Type | Description |
|---|---|---|
| feature 1 | VirtualArray | First measurable property or characteristic of the data points being analyzed (e.g elevation, gradient norm, etc... |
| feature 2 | VirtualArray | First measurable property or characteristic of the data points being analyzed (e.g elevation, gradient norm, etc... |
| feature 3 | VirtualArray | Third measurable property or characteristic of the data points being analyzed (e.g elevation, gradient norm, etc... |
Outputs
| Name | Type | Description |
|---|---|---|
| output | VirtualArray | Cluster labelling. |
Parameters
| Name | Type | Description |
|---|---|---|
| nclusters | Integer | Number of clusters. |
| normalize_inputs | Bool | Determine whether the feature amplitudes are normalized before the clustering. |
| Seed | Random seed number | Random seed number. The random seed is an offset to the randomized process. A different seed will produce a new result. |
| weights.x | Float | Weight of the first feature. |
| weights.y | Float | Weight of the third feature. |
| weights.z | Float | TODO |
Example
Corresponding Hesiod file: KmeansClustering3.hsd. Use [Ctrl+I] in the node editor to import a hsd file within your current project.
Note
Example files are kept up-to-date with the latest version of Hesiod. If you find an error, please open an issue.