Machine Learning-based High-Dimensional Text Document Classification and Clustering
- By Ansh Kataria1
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View Affiliations Hide Affiliations1 Centre for Interdisciplinary Research in Business and Technology, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Source: Demystifying Emerging Trends in Machine Learning , pp 139-149
- Publication Date: February 2025
- Language: English
Machine Learning-based High-Dimensional Text Document Classification and Clustering, Page 1 of 1
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Text classification is a difficult technique. Many techniques have been developed to decrease the dimension of feature vectors for use in text classification due to their enormous size. This work provides a detailed discussion of unique parameters utilising an optic clustering strategy, as well as a review of some of the most essential text categorization algorithms. In this case, the words are clustered according to their level of similarity. Each cluster's membership function is based on the mean along with the standard deviation of its data. Finally, characteristics are chosen from each grouping. Each cluster's extracted feature is the weighted sum of its words. There's also no need to guess or use trial-and-error approaches to determine the optimal number of clusters.
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