Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.
Evaluation must be done on test data that are independent of the training data (usually a disjoint set of instances).
Sometimes use cross-validation (averaging results over multiple training and test splits of the overall data)
It’s easy to get good performance on a test set that was available to the learner during training (e.g., just memorize the test set).
Measures: precision, recall, F1, classification accuracy
Classification accuracy: c/n where n is the total number of test instances and c is the number of test instances correctly classified by the system.
Adequate if one class per document
Otherwise F measure for each class
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License