+1 also needed for doccat.
Maybe it can be created by a class which could also
be used for doccat.
Jörn
On 02/26/2012 03:13 AM, Jason Baldridge wrote:
+1 Fine-grained error analysis FTW!
On Sat, Feb 25, 2012 at 4:57 PM, [email protected]<
[email protected]> wrote:
Hi,
I implemented a new EvaluationMonitor for the POS Tagger. It generates
a confusion
matrix<http://en.wikipedia.org/wiki/Confusion_matrix> for each token that
was not tagged properly.
Example output (Portuguese):
...
Accuracy for [que]: 91,34%
1316 ocurrencies. Confusion matrix (line: reference; column: predicted):
| conj-s | pron-indp | adv | pron-det || % Accu ||
conj-s |> 537<| 40 | 0 | 0 || 93,07% ||
pron-indp | 59 |> 661<| 0 | 0 || 91,81% ||
adv | 2 | 12 |> 4<| 0 || 22,22% ||
pron-det | 0 | 1 | 0 |> 0<|| 0% ||
Accuracy for [o]: 98,48%
3949 ocurrencies. Confusion matrix (line: reference; column: predicted):
| art | pron-det | pron-pers | , || % Accu ||
art |> 3857<| 4 | 0 | 1 || 99,87% ||
pron-det | 36 |> 24<| 0 | 0 || 40% ||
pron-pers | 19 | 0 |> 8<| 0 || 29,63% ||
, | 0 | 0 | 0 |> 0<|| 0% ||
Accuracy for [a]: 96%
4395 ocurrencies. Confusion matrix (line: reference; column: predicted):
| art | prp | pron-pers | pron-det || % Accu ||
art |> 3291<| 54 | 0 | 0 || 98,39% ||
prp | 107 |> 922<| 0 | 0 || 89,6% ||
pron-pers | 4 | 0 |> 4<| 0 || 50% ||
pron-det | 11 | 0 | 0 |> 2<|| 15,38% ||
...
Do you think it is interesting to make this report available?
I would add it to the CLI and it would be activated by an new argument that
pass in an output file for the report.
Thank you,
William
