Find leukemia clusters

Choose Detect Boundary > Constrained Clustering from the Data menu OR after right clicking on the dataset.

  1. General Tab

    1. Data: leukemia

    2. Clear the box next to "measure goodness of fit for multiple partitions" (or leave it cleared).

    3. Choose a name for the clusters dataset and the new boundary.

      1. 205 Clusters

      2. 205 Cluster Boundary

    4. Choose a target number of clusters: 205.

    5. Choose to detect boundaries using a single variable. Choose Cases/1000.

    6. Choose not to standardize data before detection (clear the checkbox). Data standardization is only necessary when you analyze multiple variables.

  2. Advanced Tab:

    1. Retain Squared Euclidean distance.

    2. Retain linkage clustering.

    3. Set the connectedness parameter to 0.8.   This setting asks BoundarySeer to compare adjacent clusters based on the more dissimilar elements in each cluster before deciding whether to merge them. This is a more stringent setting than lower connectedness.

    4. Do not choose to subsample the data.

    5. Choose to cluster with the k-means refinement (checked as a default).

  3. Hit "OK".

  4. View Boundary: Choose to view the clusters and boundary in Map1. (It will take BoundarySeer a few moments to load).

  5. Interpret map and table output.

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