A confusion matrix summarises the performance of the model on this evluation dataset. All figures in the table are percentages and are calculated across the predicitions made by the model for each observation and compared to the actual or known values of the target variable. The first column reports the true negative and false negative rates whilst the second column reports the false positive and true positive rates.
The Error column calculates the error across each class. We also report the overall error which is calculated as the number of errors over the number of observations. The average of the class errors is also reported.
Predicted Actual no yes Error no 69.6 9.5 12.0 yes 8.8 12.2 41.9 Overall error: 18% Average class error: 27%
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