A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions

Despite the availability and ease of collecting a large amount of free, unlabeled data, the expensive and time-consuming labeling process is still an obstacle to labeling a sufficient amount of training data, which is essential for building supervised learning models. Here, with low labeling cost, t...

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Bibliographic Details
Main Authors: Alaa Tharwat, Wolfram Schenck
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/11/4/820