{"product_id":"statistical-inference-from-high-dimensional-data-9783036509440","title":"Statistical Inference from High Dimensional Data","description":"\u003cp\u003e • Author(s): Carlos Fernandez-Lozano\u003cbr\u003e • Publisher: Mdpi AG\u003cbr\u003e • Publisher Imprint: Mdpi AG\u003cbr\u003e • BISAC: Life Sciences - Biology\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e- 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\u003c\/p\u003e","brand":"Mdpi AG","offers":[{"title":"Hardcover","offer_id":45414438535319,"sku":"9783036509440","price":6082.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783036509440.webp?v=1767920211","url":"https:\/\/atlanticbooks.com\/products\/statistical-inference-from-high-dimensional-data-9783036509440","provider":"Atlantic Books","version":"1.0","type":"link"}