<s>[INST] Here's a publically availible dataset Link : https://publicdata.cims.nyu.edu/files/Pratt_Milstein/Similarity_Clust/

Description:
This dataset is used to evaluate similarity measures for clustering tasks.. Each file represents a different type of similarity and has a different number of clusters (from 20 to 40). 
There are 6 files which denote 6 methods -  Star (linear), Animal (low variation in Subject), Animal (medium variation in Subject), Animal (high variation in similarity), Car (low variation in similarity), Car (high variation in similarity).
For each method, the 2500 points each have their own unique identifier.

I am trying to visualise and present the clusters derived from the data using Dimensionality Reduction techniques.

Also what are some preprocessing steps that I need to be aware of?[/INST]