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
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%

Press Enter to continue: 


Your donation will support ongoing development and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984.
Copyright © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0.