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Data-centric approaches to multi-label classification
AI systems are well-suited to tasks involving recognizing and predicting data patterns. Supervised classification systems categorize unseen data into a finite set of discrete classes by learning from millions of hand-labeled labeled sample points. These classifiers are powerful business tools – they automate document sorting, customer sentiment analysis, sales performance, and other distinct business problems. However, they also require an…
