Creates a table showing the observed and predicted values, as a heatmap. This is also referred to as a confusion matrix, classification-accuracy, and hit-miss table.
A predictive model such as regression, linear discriminant, random forest or any other machine learning model generated in Q.
To generate the prediction accuracy table:
- Select the machine learning model output.
- Select Create > Classifier > Diagnostic > Prediction-Accuracy Table.
Creates a table showing the observed and predicted values, as a heatmap.
The footer of the table firstly describes the data that were used to fit the model. In this example there were 149 cases in the 70% of data used for training, of which only 116 were used after removing cases with missing values. It then gives the accuracy for the prediction data and a count of the number of predictions that are paired with observations (after accounting for missing values in the prediction data).
This blog post includes an example of a prediction-accuracy table.