Abstract
Dimensionality reduction is used to reduce the number of features under consideration, where each feature is a dimension that partly represents the data objects. Dimensionality reduction methods make sure that all the relevant information remains intact while mapping data from a higher dimension to lower dimension.
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Thomas, T., P. Vijayaraghavan, A., Emmanuel, S. (2020). Dimensionality Reduction and Face Recognition. In: Machine Learning Approaches in Cyber Security Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-15-1706-8_7
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DOI: https://doi.org/10.1007/978-981-15-1706-8_7
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