RandolphVI/Multi-Label-Text-Classification
About Muti-Label Text Classification Based on Neural Network.
This project helps you automatically categorize text documents or short texts by assigning multiple relevant labels to each. You input a collection of text documents (like news articles, product reviews, or scientific papers) and define a set of possible labels. The output is each text tagged with all applicable labels. This is ideal for analysts, content managers, or researchers who need to organize and analyze large volumes of text data with multiple descriptive categories.
561 stars. No commits in the last 6 months.
Use this if you need to classify text into several categories simultaneously, for instance, tagging a single legal document with 'contract', 'litigation', and 'real estate' all at once.
Not ideal if your classification task only requires assigning a single label to each text, or if you need to classify non-textual data.
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Language
Python
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Apache-2.0
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Last pushed
Nov 18, 2020
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