Statistical Inference from High Dimensional Data
- ISBN-10
- 3036509445
- ISBN-13
- 9783036509440
- Category
- Science
- Pages
- 314
- Language
- English
- Published
- 2021-04-28
- Publisher
- MDPI
- Author
- Carlos Fernandez-Lozano
Description
• Real-world problems can be high-dimensional, complex, and noisy • More data does not imply more information • Different approaches deal with the so-called curse of dimensionality to reduce irrelevant information • A process with multidimensional information is not necessarily easy to interpret nor process • In some real-world applications, the number of elements of a class is clearly lower than the other. The models tend to assume that the importance of the analysis belongs to the majority class and this is not usually the truth • The analysis of complex diseases such as cancer are focused on more-than-one dimensional omic data • The increasing amount of data thanks to the reduction of cost of the high-throughput experiments opens up a new era for integrative data-driven approaches • Entropy-based approaches are of interest to reduce the dimensionality of high-dimensional data
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