In statistical theory, the field of high-dimensional statistics studies data whose dimension is larger (relative to the number of datapoints) than typically considered in classical multivariate analysis.

Feb 10, 2021 · This tutorial provides an explanation of high dimensional data, including a formal definition and several examples.

Nov 14, 2024 · What is High-Dimensional Data? High-dimensional data refers to datasets that contain a large number of features or variables relative to the number of observations or samples.

High Dimensional Data - an overview | ScienceDirect Topics

High-dimensional statistics focuses on data sets in which the number of features is of comparable size, or larger than the number of observations. Data sets of this type present a variety of new challenges, …

Information and technology have revolutionized data collection. High-dimensional data, including, but not limited to, genetic data, image data such as Magnetic resonance imaging (MRI) and functional MRI, …

Dec 18, 2024 · High-dimensional data contains a large number of features, often exceeding the number of observations. This type of data is common in fields like genomics, text analysis, and image …

We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction of high-dimensional data sets, and multi …

Mathematically, data is a subset A ⊆ Rd where the dimension d is typically a very large number. Concrete examples are as follows. A greyscale picture with 320 × 240 pixel can be described by 75 …

Analyzing data when variables exceed observations. High-dimensional statistics addresses the unique challenges and theoretical foundations of analyzing data where the number of variables is very large, …