ISOMAP is a non-linear dimensionality reduction technique that aims to preserve the intrinsic geometry of high-dimensional data in a lower-dimensional space. It is particularly useful for data with ...

In this paper, the Isometric Mapping (ISOMAP) algorithm is applied to recognize oracle bone inscription images. First, the sample set undergoes denoising and size normalization as preprocessing steps.

Abstract: Isomap borrows the idea of geodesics which is from differential geometry, hoping data can keep geodesic distance on the manifold after transforming into low dimensional space mapping. Isomap ...

ABSTRACT: In dealing with high-dimensional data, such as the global climate model, facial data analysis, human gene distribution and so on, the problem of dimensionality reduction is often encountered ...

Abstract: As for the difficult problem of sensitive feature extraction during fault prediction for nonlinear electromechanical equipment, nonlinear dimensionality reduction ISOMAP (isometric feature ...

Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear. Microarray data is one ...

The objective of this question is to reproduce the ISOMAP algorithm results that we have seen discussed in lecture as an excercise. The file isomap.mat (or isomap.dat) contains 698 images, ...

Outlier detection in high-dimensional datasets is a fundamental and challenging problem across disciplines that has also practical implications, as removing outliers from the training set improves the ...

This paper also establishes a combined Isomap–ACO–ET prediction model combing the Isomap algorithm (Isomap), Ant Colony Algorithm (ACO), and Extreme Random Tree Algorithm (ET) based on the indicator ...