Regression - Diagnostic - Prediction-Accuracy Table
Creates a table showing the observed and predicted values, as a heatmap.
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.
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");
main();
function main() {
// The following 2 variables contain information specific to this diagnostic.
var required_class = ["MachineLearning", "MachineLearningEnsemble", "Regression"];
var output_name_suffix = "prediction.accuracy.table";
var item = checkSelectedItemClass(required_class);
if (item == null)
return false;
var r_name = stringToRName(item.referenceName);
// The following lines contain the R code to run
var expression = "library(flipRegression)\nConfusionMatrix(" + r_name + ", QFilter, QPopulationWeight)";
return createROutput(item, expression, output_name_suffix);
}
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