To measure the performance of a classification algorithms on a dataset that has an attribute for class type, I divide my dataset to training and test samples and then create a
confusion matrix for
True Positive and
True Negative samples. Hence there is a class type attribute(e.g
No ), the confusion matrix is pretty easy to calculate.
Now suppose that I have a dataset that lacks a class type attribute and all samples are of the class
How can I measure the performance of different classification algorithms using these kind of datasets?