Test Metrics for Classification Models

Test metrics assess how accurately the model predicts the known values. Test settings specify the metrics to be calculated and control the calculation of the metrics. By default, Oracle Data Miner calculates the following metrics for Classification models:

• Performance measurements, Predictive Confidence, Average Accuracy, Overall Accuracy, and Cost

• Performance Matrix, also know as Confusion Matrix

• Receiver Operating Characteristics

• Lift

• Profit and ROI

You can change the defaults using the preference setting.

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

• If you tested the models using the default test in the Classification node:

  1. Run the Classification node.

  2. Right-click the node and select View Test Results.

  3. To view the model, select the model that you are interested in. The Classification Model Test View opens.

  4. To compare the test results for all models in the node, select Compare Test Results.

• If you tested the models using a Test node:

  1. Run the Test node.

  2. Right-click the node and select View Test Results.

  3. To view the model, select the model that you are interested in. The Classification Model Test View opens.

  4. To compare the test results for all models in the node, select Compare Test Results.