Extreme learning machine (ELM), as a new learning method for training feedforward neural networks, has shown its good generalization performance in regression and classification applications. Random projection (RP), as a simple and powerful technique for dimensionality reduction, is used for projecting high-dimensional data into low-dimensional subspaces while ensuring that the distances between data points are approximately preserved. This paper presents a systematic study on the application of RP in conjunction with ELM for both low-and high-dimensional data classification and clustering.
CITATION STYLE
Alshamiri, A. K., Singh, A., & Surampudi, B. R. (2015). Combining ELM with random projections for low and high dimensional data classification and clustering. In Advances in Intelligent Systems and Computing (Vol. 415, pp. 89–107). Springer Verlag. https://doi.org/10.1007/978-3-319-27212-2_8
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