Processes | Pattern Discovery | Multidimensional Scaling

Multidimensional Scaling
The Multidimensional Scaling (MDS) process estimates the coordinates of a set of objects in a space of specified dimensionality that come from data measuring the distances between pairs of objects. The input data is usually a distance matrix, which can be created by the Distance Matrix and Clustering process. A 2D or 3D Scatterplot is generated based on the estimated coordinates.
MDS can be used as a data exploration tool to identify grouping patterns in the data.
For a more detailed description of MDS, refer to the SAS/STAT reference manual on PROC MDS.
What do I need?
One Input Data Set is required to run the Multidimensional Scaling process. This data set should be a square matrix. The adsl_diit_dmt.sas7bdat data set (from the included Nicardipine data) contains a square matrix.
The adsl_diit_dmt.sas7bdat data set was generated as previously described (see Distance Matrix and Clustering) from the adsl_diit.sas7bdat data set included with JMP Clinical.
For detailed information about the files and data sets used or created by JMP Life Sciences software, see Files and Data Sets.
The output generated by this process is summarized in a Tabbed report. Refer to the Multidimensional Scaling output documentation for detailed descriptions and guides to interpreting your results.