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!

まず t_stochastic_neighbour_embedding.py と現在の TSNE の使用方法を読みます。可視化、再現性、パラメーター、import 処理に関して提案されている変更を確認し、どの提案を対象範囲に含めるかを確定します。選択した改善が実装され、スクリプトが引き続き期待どおりに実行されれば完了です。