Comparing the Confusion
of Multi-Label Classifiers

Hello everyone! I will help you to compare the results of two different classifiers trained on the same multi-label dataset. This means you can find similarities and differences in the confusion to decide which classifier to use preferably, or to figure out how to combine these classifiers in ensemble learning methods.

CHOOSE YOUR DATA

Go with an example configuration:

Upload your own data:

Information about the training dataset

Name of dataset

Link to dataset

Description for dataset

Instance type (e.g., Reddit comment) *

Classification task category *

Classifier A

Name of classifier A

Link to classifier A

Description for classifier A

Classifier B

Name of classifier B

Link to classifier B

Description for classifier B

Upload of the classification results

Ground truth* :

Dataset A* :

Dataset B*:

Comparing the Confusion of Multi-Label Classifiers

CHOOSE YOUR DATA

Comparing the Confusion
of Multi-Label Classifiers