Multi Dimensional Scaling
Last updated
Last updated
Calculates coordinations by reducing dimensionality using SVD (Singular Value Decomposition).
You can access from 'Add' (Plus) button.
Name1 Column - Set one of name columns to calculate coordinations for.
Name2 Column - Set another column of names to calculate coordinations for.
Value Column (Optional) - Set a column to use as a distance value. If you use do_dist in the previous step, this will be value.
Number of Dimensions (Optional) - The default is "group".
"group" is to see how groups are projected to a new coordinations. This corresponds to u matrix of svd.
"dimension" is to see what direction the new coordinations face. This corresponds to v matrix of svd.
"variance" is to see how data is scattered in each of the new coordinations. This corresponds to d vector of svd. itself.
n_component (Optional) - The default is 3. Set number of dimensions to reduce to. This must be less than the number of subjects and the number of keys.
Number of Dimensions (Optional) - The default is TRUE. Set if data should be centralized to the origin.
Centralize Data - Whether data should be centralized or not.
Output Format (Optional) - The default is "wide".
"wide" - The components will be in columns.
"long" - The component will be in row.
Take a look at the reference document for the 'svd' function from base R for more details on the parameters.
