Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with multi-class
Search options answers only
not deleted
user 12359
Multiclass classification is a classification task in which there are more than two classes. It is also called multinomial classification.
32
votes
Multilabel classification metrics on scikit
The subset accuracy is indeed a harsh metric. To get a sense of how good or bad 0.29 is, some idea:
look at how many labels you have an average for each sample
look at the inter-annotator agreement, …
- 47.6k
7
votes
Accepted
Accuracy vs Jaccard for multiclass problem
The issue has been reported on scikit-learn GitHub repository: multiclass jaccard_similarity_score should not be equal to accuracy_score #7332
scikit-learn's Jaccard score for the multiclass classifi …
- 47.6k
33
votes
What is the difference between a multiclass and a multilabel problem?
To complement the other answers, here are some figures. One row = the expected output for one sample.
Multiclass
One column = one class (one-hot encoding)
Multilabel
One column = one class
…
- 47.6k
5
votes
Accepted
Training N classifiers for N labels vs one classifier with N labels
It mostly depends on your labels. Training one classifier with N labels (= multitask) makes more sense when labels are related. But one cannot predict in advance with 100% certainty whether multitask …
- 47.6k