"Interpretation/Meaning of Performance Measure"

choose_username

Hello,

i have build a workflow, which shall classify examples with a decision tree. I used a Performance-measure-Operator too. In the result are accuracy , precision and recall listed.

What does this measures mean? Is there a difference between accuracy and precision and what is the meaning of recall?

greetings

user

IngoRM

Hi,

those measures are all taken from a confusion matrix (http://en.wikipedia.org/wiki/Confusion_matrix):

	Actually Positive	Actually Negative
Predicted Positive	a	b
Predicted Negative	c	d

After the prediction, RapidMiner checks for each example the true label and the prediction and sorts the example into the correct place in the confusion matrix, i.e. increases the count by 1. The sum of a,b,c, and d hence is the total number of examples. The value "a" is called "true positives", "b" is called "false positives", "c" is called "false negatives", and "d" is called "true negatives".

The ratio of correctly classified examples compared to the number of all examples is called accuracy and is calculated as (a+d)/(a+b+c+d).

The ratio of true positives to all as positive predicted examples is called precision and is calculated as a / (a+b).

The ratio of true positives to all actually positive examples is called recall and is calculated as a / (a+c).

Accuracy is also available in the case of more than two classes, precision and recall are only available for two-class-problems (you can, however, always calculate a per class precision and recall).

Cheers,
Ingo