Classification Rate
Ratio of correctly classified rows to the total number or rows.
For classification predictive models, it corresponds to the ratio of correctly classified rows
to the total number of rows.
Example
A classification rate of 0.82 means that 82% of
the rows in the training dataset are correctly classified by the predictive
model.Note
The classification rate is not very well adapted to
unbalanced cases, when the target category is not very frequent. For example, if
there is only 1% of the target category, it's very easy to have a very high
classification rate. In such a case, check the Predictive Power or the Area Under
the ROC Curve (AUC).