Testing Regression Models

Regression models are tested by comparing the predicted values to known target values in a set of test data. The historical data for a regression project is typically divided into two data sets: one for building the model and one for testing the model.

The test data must be compatible with the data used to build the model and must be prepared in the same way that the build data was prepared.

These are the ways to test classification and regression models:

The test tab defines how tests are done. The default is to test all models built.

By default, the test data is created by randomly splitting the build data into two subsets; 40% if the input data is used for the test set. You can also use all of the build data for testing.

Test settings specify which metrics to calculate and control the calculation of the metrics.

Oracle Data Mining provides several kinds of information to assess regression models:

To view test results, first test the model or models in the node:

You can also compare test results by going to the Models section of Properties of the Build node where you tested the models and clicking compare models