ISOMAP is a non-linear technique for dimension reduction which allows you to find relationships in an unordered dataset.

## What do we mean by *non-linear?*

As opposed to other linear techniques used for **dimension reduction** like PCA or SVD, data points that, in appearence, are close to each other (small *Euclidean* distance) could in fact be farther (*Geodesic* distance)

In the Swiss Roll picture below, the red and blue dots are very close in terms of the *Euclidean* distance, but very far in the *Geodesic* distance.

If you find this interesting, you can take a look at the following link. With the help of R and the “RDRToolbox” package I’ve developed this Cool Shiny.