Includes recipes that demonstrate how to complete specific analysis.
Comparing aggregated data for two different time periods can help to identify patterns and changes in data.
You can determine the relationship of two items based on the amount of times the items were bought in the same transaction, the number of transactions that contained each item individually and the amount of transaction over all.
Using 1010data's g_function, g_pca(G;S;XX;Z), you can create a model that corresponds to the principal component analysis of one or more variables. However, in order to determine the loadings/eigenvectors you need to use param(M;'evecs';J I).
g_pca(G;S;XX;Z)
param(M;'evecs';J I)
