Feedback on t-SNE script: ideas to improve clarity and usability

Feature description

Hi! I tested your t_stochastic_neighbour_embedding.py script on my local setup and it runs well thanks for sharing it!

I have a few suggestions that might improve clarity and usability for others:

Visualization: Consider adding a matplotlib scatter plot to show the t-SNE result. It helps users see the clustering visually.

Reproducibility: Adding random_state=42 to the TSNE() constructor would make the output consistent across runs.

Parameter transparency: Explicitly setting perplexity, learning_rate, and n_iter could help learners understand how t-SNE behaves.

Import error handling: A simple try/except block for sklearn imports could guide users if they haven't installed the package.

Let me know if you'd like help implementing any of these — happy to collaborate!

Commencez par lire t_stochastic_neighbour_embedding.py et l’utilisation actuelle de TSNE. Examinez les modifications proposées concernant la visualisation, la reproductibilité, les paramètres et la gestion des imports, puis confirmez quelles suggestions sont dans le périmètre. C’est terminé lorsque les améliorations sélectionnées sont implémentées et que le script continue de s’exécuter comme prévu.