Machine Learning - Diagnostic - Prediction-Accuracy Table
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Q Technical Reference
Q Technical Reference
Q Technical Reference > Setting Up Data > Creating New Variables
Q Technical Reference > Updating and Automation > Automation Online Library
Q Technical Reference > Updating and Automation > JavaScript > QScript > QScript Examples Library > QScript Online Library
R Online Library
User Interface > Create Classifier
User Interface > Create Machine Learning
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.
This blog post includes an example of a prediction-accuracy table.
Example
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).
Code
includeWeb("QScript R Output Functions");
const menu_location = "Machine Learning > Diagnostic > Prediction-Accuracy Table";
createDiagnosticROutputFromSelection(menu_location);
Q Technical Reference
Q Technical Reference
Q Technical Reference > Setting Up Data > Creating New Variables
Q Technical Reference > Updating and Automation > Automation Online Library
Q Technical Reference > Updating and Automation > JavaScript > QScript > QScript Examples Library > QScript Online Library
R Online Library
User Interface > Create Classifier
User Interface > Create Machine Learning