Finding the needles in a haystack of high-dimensional data sets

One of the challenges in the era of Big Data is dealing with many independent variables, also known as the "curse of dimensionality." Therefore, there is an urgent need to develop algorithms that can select subsets of features that are relevant and have high predictive powers. To address this issue, computer scientists at the University of Groningen developed a novel feature selection algorithm. The description and validation of their method was published in the journal Expert Systems with Applications on 16 September 2021.

from News on Artificial Intelligence and Machine Learning https://ift.tt/3zAo69r

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