Projections are conventional methods of dimensionality reduction for information visualization used to transform high-dimensional data into low dimensional space. If the projection method restricts the output space to two dimensions, the result is a scatter plot.
Practical conclusion: When looking for projections that tell you something interesting about the data, look for something that is very different from Gaussian.
Missing: Explaining | Show results with:Explaining
People also ask
How do you define high-dimensional data?
What is a common technique used to represent high-dimensional image data?
How to visualize high-dimensional data by using statistical methods?
What is dimensional projection?
Jan 31, 2024 · Projecting data into high-dimensional space often results in improved model performance, especially when dealing with complex datasets.
Missing: Explaining | Show results with:Explaining
We present a set of interactive visual analysis techniques aiming at explaining data patterns in multidimensional projections.
Nov 26, 2015 · Projecting high-dimensional data into a lower-dimension space helps to preserve the actual pair-wise distances (mainly Euclidean one) which get ...
High-dimensional data means that we have a large number of numeric features or variables, which can be considered as dimensions in a mathematical space.
This thesis aims to answer the question how to adequately explain these patterns in projections of high-dimensional data, while simultaneously scaling better ...
Aug 3, 2013 · I'm trying to project a set of 13-dimensional vectors to n (n = 1,2,3) dimensional space for visualization purposes.
Apr 2, 2019 · How to visualize features of more than 3 data dimensions at once.
Mar 25, 2024 · This book provides guidance on visualising high-dimensional data and models using linear projections, with R. High-dimensional data spaces are ...
Missing: Explaining | Show results with:Explaining