This is an excerpt from Dr. Ham's premier book "Oracle
Data Mining: Mining Gold from your Warehouse".
Next, we select the apply data source that we created as MINING_DATA_BUILD_V_NOUS
in Step 2 of the Apply Data wizard, and click Next.
Now you have the option of selecting additional columns to be included in the
table resulting from the Apply operation. The wizard suggests that you include
the customer identity attribute so that you can see which customers are most
likely to have an affinity card.
By
default, the “Apply Result” contains only the case identifier and prediction
information. You may want to keep the “bare bones” set of predictor variables
and join this with tables containing the customer contact information later.
Select some or all of the attributes in Step 3, and click Next.
The next step allows you to choose the format for the output
table. When the model is applied to a particular customer, a score is generated
for each possible target value. A sorted list is generated from the most to
least likely value. This list will have only two entries since our target is a
binary, because our customers either have or do not have an affinity card.
Viewing Top Rankings
If your target had multiple results, as in the case of
predicting which of 10 stores a customer was most like to shop, then you might
want to see the ranking of top three choices for each customer, and would click
the radio button next to “Number of Best Target Values” and enter in 3. The
output table would have three rows for each individual containing the prediction
information for the top three stores.
In the case of which of ten stores the customer is most
likely to shop, you may only be interested in a customer’s ranking probability
for a particular store. Then you would check the radio button next to “Specific
Target Values” and check the box next to the particular store you were
interested in. The result would be a table with one row for each customer with
the prediction for that store, even though the probability might be extremely
low.
Using the Classification Apply
Option
