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Unsupervised feature selection using feature similarity
Abstract
In this article, we describe an unsupervised feature selection algorithm suitable for data sets, large in both dimension and size. The method is based on measuring similarity between features whereby redundancy therein is removed. This does not need any search and, therefore, is fast. A new feature similarity measure, called maximum information compression index, is introduced. The algorithm is generic in nature and has the capability of multiscale representation of data sets. The superiority of the algorithm, in terms of speed and performance, is established extensively over various real-life data sets of different sizes and dimensions. It is also demonstrated how redundancy and information loss in feature selection can be quantified with an entropy measure.
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Cited by
A survey on feature selection methods
Chandrashekar, G., & Sahin, F. (2014) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.11.024 · Cited by 5,189
Ghamisi, P., Yokoya, N., Li, J., Liao, W., Liu, S., Plaza, J., Rasti, B., & Plaza, A. (2017) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2017.2762087 · Cited by 909
Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification
Sathya, R., & Abraham, A. (2013) · International Journal of Advanced Research in Artificial Intelligence · doi:10.14569/ijarai.2013.020206 · Cited by 459
MIFS-ND: A mutual information-based feature selection method
Hoque, N., Bhattacharyya, D. K., & Kalita, J. K. (2014) · Expert Systems with Applications · doi:10.1016/j.eswa.2014.04.019 · Cited by 442
Content-based image retrieval: approaches and trends of the new age
Datta, R., Li, J., & Wang, J. Z. (2005) · Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval · doi:10.1145/1101826.1101866 · Cited by 435
Metadata
- Authors
- Mitra, P., Murthy, C. A., & Pal, S. K.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2002-03
- Volume
- 24
- Issue
- 3
- Pages
- 301-312
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2060542593
- Cited by
- 1,460
- References
- 0
- FWCI
- 19.10
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mitra, P., Murthy, C. A., & Pal, S. K. (2002). Unsupervised feature selection using feature similarity. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.990133
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