A comparative study on dimensionality reduction between principal component analysis and k-means clustering
The curse of dimensionality and the empty space phenomenon emerged as a critical problem in text classification. One way of dealing with this problem is applying a feature selection technique before performing a classification model. This technique helps to reduce the time complexity and sometimes i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2019
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |