See also
Taxonomy benchmark home
Validating taxonomy classifiers
Training taxonomy classifiers
UTAX algorithm
Splitting a taxonomy reference set
Defining "accuracy" of a taxonomy classifier
False positive error
Classifier predicts an incorrect taxon for the given level (family, genus
etc.).
Misclassification error
Type of false positive error. Classifier predicts a wrong name at the given
level (family, genus etc.) when at least one reference sequence for the correct
taxon is present in the training set.
Overclassification error
Type of false positive error. Classifier predicts a name at the given level
(family, genus etc.) when there are no reference sequences for the correct taxon
in the training set. See taxonomy
overclassification and underclassification errors for further discussion.
False negative error
Classifier does not predict a name for the given taxon (family, genus etc.)
when at least one reference sequence for the correct taxon is in the training
set.
Underclassification error
Classifier does not predict a name at the
given level (family, genus etc.) when there are reference sequences for the
correct taxon in the training set. See taxonomy
overclassification and underclassification errors for further discussion.
All false negatives are underclassification errors so there is really no need
for a new term.
| Taxon is present in training data | Taxon is predicted by classifier | Correct name is predicted | Correct / Error | Result |
| Yes | Yes | Yes | Correct | True positive |
| Yes | Yes | No | Error |
False positive (misclassification) |
| Yes | No | - | Error | False negative (underclassification) |
| No | Yes | - | Error |
False positive (overclassification) |
| No | No | - | Correct | True negative |