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Published in 2017 at "Scientific Reports"
DOI: 10.1038/s41598-017-11873-y
Abstract: Analyzing large volumes of high-dimensional data is an issue of fundamental importance in data science, molecular simulations and beyond. Several approaches work on the assumption that the important content of a dataset belongs to a…
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Keywords:
dimension;
estimating intrinsic;
datasets minimal;
intrinsic dimension ... See more keywords
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Published in 2017 at "Neural Computation"
DOI: 10.1162/neco_a_00969
Abstract: We propose a method for intrinsic dimension estimation. By fitting the power of distance from an inspection point and the number of samples included inside a ball with a radius equal to the distance, to…
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Keywords:
dimension;
estimation generalized;
dimension estimation;
intrinsic dimension ... See more keywords
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Published in 2021 at "Entropy"
DOI: 10.3390/e23101368
Abstract: Dealing with uncertainty in applications of machine learning to real-life data critically depends on the knowledge of intrinsic dimensionality (ID). A number of methods have been suggested for the purpose of estimating ID, but no…
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Keywords:
package;
dimension;
estimation;
python package ... See more keywords