Dimensionality reduction is a hot research topic in data analysis today.Thanks to the advances in high-performance computing technologies andin the engineering eld, we entered in the so-called big-data era and an enormous quantity of data is available in every scientificc area, rangingfrom social networking, economy and politics to e-health and life sciences.However, much of the data is highly redundant and can be efficientlybrought down to a much smaller number of variables without a significantloss of information using didifferent strategies.
Dimensionality Reduction
Italia De Feis
2019
Abstract
Dimensionality reduction is a hot research topic in data analysis today.Thanks to the advances in high-performance computing technologies andin the engineering eld, we entered in the so-called big-data era and an enormous quantity of data is available in every scientificc area, rangingfrom social networking, economy and politics to e-health and life sciences.However, much of the data is highly redundant and can be efficientlybrought down to a much smaller number of variables without a significantloss of information using didifferent strategies.File in questo prodotto:
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