Title:
Combining Classification and Clustering Tasks to Categorize Known and Unknown Classes
Combining Classification and Clustering Tasks to Categorize Known and Unknown Classes
Authors
Shabbir, Javeria
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Kira, Zsolt
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Abstract
Since the past few years research has been directed towards the training of neural networks
using unlabeled data or pairwise pseudo constraints known as unsupervised learning and
semi-supervised learning respectively. In this thesis, we explored several methods to improve the performance of the current state-of-the-art algorithm for unsupervised learning
called SCAN using semi-supervision from pairwise pseudo constraints.
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Date Issued
2022-12-19
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Thesis