Exercise

# Computing t-SNE

As we have seen, the t-SNE embedding can be computed in R using the `Rtsne()`

function from the `Rtsne`

package in CRAN. Performing a PCA is a common step before running the t-SNE algorithm, but we can skip this step by setting the parameter `PCA`

to `FALSE`

. The dimensionality of the embedding generated by t-SNE can be indicated with the `dims`

parameter.

In this exercise, we will generate a three-dimensional embedding from the `mnist_sample`

dataset without doing the PCA step and then, we will plot the first two dimensions.

The MNIST sample dataset `mnist_sample`

, as well as the `Rtsne`

and `ggplot2`

packages, are already loaded.

Instructions

**100 XP**

- Compute the t-SNE embedding in three dimensions without doing a PCA step for the
`mnist_sample`

dataset excluding the`label`

column. - Inspect the obtained embedding coordinates which are stored in the
`Y`

property of the output object. - Create a data frame containing only the first two embedding coordinates as well as the true
`label`

of the MNIST digits. - Plot these coordinates using
`ggplot()`

. Give the points a label and color based on the value of the`digit`

.