GitHub - Divya171997/Text-Analytics-eXtreme-Multi-Label-Classification-XMLC: Multi-label classification is one of the standard tasks in text analytics. The objective is to perform an eXtreme multi-label classification (XMLC) on two datasets( https://www.kaggle.com/hsrobo/titlebased-semantic-subject-indexing) -EconBiz( ZBW - Leibniz Information Centre for Economics from July 2017) and PubMed(5th BioASQ challenge on large-scale semantic subject indexing of biomedical articles).In an XMLC setting, there are k many labels from a large pool of n labels to be assigned to the data objects. The classification task is extreme in two senses: First, the number of n labels is very large with hundreds or thousands of labels. Second, there are only very few k labels to assign, i. e. it holds k <<n. Thus, it is likely to have false positives.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
CE807_Assignment2_Task1_1901423.pdf		CE807_Assignment2_Task1_1901423.pdf
CE807_Assignment2_Task3_1901423.pdf		CE807_Assignment2_Task3_1901423.pdf
Landscape_of_Text-Analytics.pdf		Landscape_of_Text-Analytics.pdf
XMLC.ipynb		XMLC.ipynb

About

Multi-label classification is one of the standard tasks in text analytics. The objective is to perform an eXtreme multi-label classification (XMLC) on two datasets( https://www.kaggle.com/hsrobo/titlebased-semantic-subject-indexing) -EconBiz( ZBW - Leibniz Information Centre for Economics from July 2017) and PubMed(5th BioASQ challenge on large-sc…

data-preprocessing evaluation f1-score feature-extraction hamming-loss load-data model-building

Activity

0 stars

1 watching

0 forks

Report repository

Navigation Menu

About

Releases

Packages

Contributors

Languages

Folders and files

Latest commit

History

About

Topics

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages