The Transaction SVD plot contains a point for each transaction. For a given transaction, the point that is plotted is defined by the transaction’s values on the first two singular vectors in U. In the Transaction SVD plot, points that are visibly grouped together indicate transactions with a similar composition. This plot is equivalent to the Score Plot in the Principal Components platform.

The Item SVD plot contains a point for each item. For a given item, the point that is plotted is defined by the item’s values on the first two singular vectors in V. In the Item SVD plot, items that are visibly grouped together indicate items that have similar functions or topic areas. This plot is equivalent to the Loadings Plot in the Principal Components platform.

See Additional Example: SVD Analysis.

Below the transaction and item SVD plots, a table of the singular values appears. These are the diagonal entries of the S matrix in the singular value decomposition of the transaction item matrix. The kth row in the Singular Values table shows the additional and cumulative percent of variability explained by using the kth singular value or singular vector column. Like in the Principal Components platform, you can use the Cum Percent column to decide what percent of variance from the transaction item matrix you want to preserve, and then use the corresponding number of singular vectors.