7.10 rain demo confusion matrix

Confusion Matrix

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

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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