MDS-class {dimRed} | R Documentation |

## Metric Dimensional Scaling

### Description

An S4 Class implementing classical scaling (MDS).

### Details

MDS tries to maintain distances in high- and low-dimensional space,
it has the advantage over PCA that arbitrary distance functions can
be used, but it is computationally more demanding.

### Slots

`fun`

A function that does the embedding and returns a
dimRedResult object.

`stdpars`

The standard parameters for the function.

### General usage

Dimensionality reduction methods are S4 Classes that either be used
directly, in which case they have to be initialized and a full
list with parameters has to be handed to the `@fun()`

slot, or the method name be passed to the embed function and
parameters can be given to the `...`

, in which case
missing parameters will be replaced by the ones in the
`@stdpars`

.

### Parameters

MDS can take the following parameters:

- ndim
The number of dimensions.

- d
The function to calculate the distance matrix from the input coordinates, defaults to euclidean distances.

### Implementation

Wraps around `cmdscale`

. The implementation also
provides an out-of-sample extension which is not completely
optimized yet.

### References

Torgerson, W.S., 1952. Multidimensional scaling: I. Theory and method.
Psychometrika 17, 401-419. https://doi.org/10.1007/BF02288916

### See Also

Other dimensionality reduction methods:
`AutoEncoder-class`

,
`DRR-class`

,
`DiffusionMaps-class`

,
`DrL-class`

,
`FastICA-class`

,
`FruchtermanReingold-class`

,
`HLLE-class`

,
`Isomap-class`

,
`KamadaKawai-class`

,
`NNMF-class`

,
`PCA-class`

,
`PCA_L1-class`

,
`UMAP-class`

,
`dimRedMethod-class`

,
`dimRedMethodList()`

,
`kPCA-class`

,
`nMDS-class`

,
`tSNE-class`

### Examples

```
## Not run:
dat <- loadDataSet("3D S Curve")
emb <- embed(dat, "MDS")
plot(emb, type = "2vars")
# a "manual" kPCA:
emb2 <- embed(dat, "MDS", d = function(x) exp(stats::dist(x)))
plot(emb2, type = "2vars")
# a "manual", more customizable, and slower Isomap:
emb3 <- embed(dat, "MDS", d = function(x) vegan::isomapdist(vegan::vegdist(x, "manhattan"), k = 20))
plot(emb3)
## End(Not run)
```

[Package

*dimRed* version 0.2.6

Index]