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Cluster
Clusters designs using the K-means algorithm and adjusts variable bounds based on each cluster. WORKS ON DOUBLECLICK
Inputs
| Name | ID | Description | Type |
|---|---|---|---|
| Variables | Var | Variables that define the design space | Number |
| Design map | DM(+O) | Data used to perform clustering | Number |
| Number of Clusters | #Clust | The objective being considered for cluster ranking | Integer |
| Flexibility | Flex | Number between 0-1 that sets the flexibility of each cluster's design space | Number |
| Cluster Index | Index | The index of the cluster being explored; 0 is entire dataset | Integer |
| Run | Run | Seperate DM into clusters | Boolean |
Outputs
| Name | ID | Description | Type |
|---|---|---|---|
| Cluster List | ClusterL | The Cluster number of each Design | Text |
| ClusterAvs | ClusterAv | Average variable values of each cluster | Text |
| ClusterMins | ClusterMins | Minimum values for each cluster | Text |
| ClusterMaxs | ClusterMaxs | Maximum values for each cluster | Text |
| ClusterObjs | ClusterObj | Average objective values for each cluster | Text |
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