tSNE {structToolbox} | R Documentation

## tSNE

### Description

t-Distributed Stochastic Neighbor Embedding.

### Usage

    tSNE(
      dims = 2,
      perplexity = 30,
      max_iter = 100,
      theta = 0.5,
      check_duplicates = FALSE,
      init = NULL,
      eta = 200,
      ...
    )

### Arguments

`dims` | (numeric) The number of tSNE dimensions computed. The default is `2`.
`perplexity` | (numeric) Perplexity parameter. The default is `30`.
`max_iter` | (numeric) The maximum number of tSNE iterations. The default is `100`.
`theta` | (numeric) Speed/accuracy trade-off. A value of 0 gives an exact tSNE. The default is `0.5`.
`check_duplicates` | (logical) Check for duplicates. Allowed values are limited to the following: `"TRUE"`: Checks for the presence of exact duplicate samples. `"FALSE"`: Does not check for exact duplicate samples. The default is `FALSE`.
`init` | (NULL, data.frame, DatasetExperiment) A set of coordinates for initialising the tSNE algorithm. NULL uses random initialisation. The default is `NULL`.
`eta` | (numeric) The learning rate parameter. The default is `200`.
`...` | Additional slots and values passed to `struct_class`.

### Details

This object makes use of functionality from the following packages:

- `Rtsne`

### Value

A `tSNE` object.

### References

van der Maaten L, Hinton G (2008). “Visualizing High-Dimensional Data Using t-SNE.” Journal of Machine Learning Research, 9, 2579-2605.

van der Maaten L (2014). “Accelerating t-SNE using Tree-Based Algorithms.” Journal of Machine Learning Research, 15, 3221-3245.

Krijthe JH (2015). Rtsne: T-Distributed Stochastic Neighbor Embedding using Barnes-Hut Implementation. R package version 0.15, https://github.com/jkrijthe/Rtsne.

### Examples

    M = tSNE()

[Package structToolbox version 1.2.0 Index]