The intrinsic dimension for a data set can be thought of as the number of variables needed in a minimal representation of the data.
The notion of intrinsic dimension (ID) intuitively refers to the minimal number of features needed to represent a dataset with little information loss. . ...
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Sep 22, 2017 · In this work we address the problem of finding the minimal number of variables needed to describe the relevant features of a dataset; this ...
Intrinsic dimension
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The intrinsic dimension for a data set can be thought of as the number of variables needed in a minimal representation of the data. Similarly, in signal processing of multidimensional signals, the intrinsic dimension of the signal describes how... Wikipedia
In this paper, we present a new estimator of intrinsic dimension, study its statistical properties, and compare it to other estimators on both simulated and ...
Definition 1. A data set ⊆ RN is said to have intrinsic dimension (ID) equal to M if its elements lie entirely, without information loss, within a M- ...
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Jun 8, 2021 · A natural question, thus, is to estimate the intrinsic dimension of a given population distribution from a finite sample.
Jan 20, 2016 · The aim of the paper is to review state-of-the-art of the methods of ID estimation, underlining the recent advances and the open problems.
Nov 21, 2022 · This article introduces a novel statistical method, Gride, that allows estimating the id as an explicit function of the scale without performing any decimation.
In this paper we present a novel method for intrinsic dimension estimation. The estimate is based on geometric properties of the data, and requires no ...
In technical terms it typically means the manifold or Hausdorff (fractal) dimension of the support of the probability distribution generating the data. This ...
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