How can you use TSNE for dimensionality reduction and visualization of high-dimensional data in Scikit-learn

Question

With the help of code can you tell me How can you use TSNE for dimensionality reduction and visualization of high-dimensional data in Scikit-learn?

Answer 1

t-SNE (t-Distributed Stochastic Neighbor Embedding) reduces high-dimensional data to 2D or 3D while preserving local structure, making it ideal for visualization.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Uses load_digits to get high-dimensional handwritten digit data.
• Reduces dimensionality from 64 to 2 with TSNE.
• Visualizes the 2D representation while preserving local structure and clustering.

Hence, t-SNE is an effective technique for visualizing high-dimensional data by revealing natural clusters and patterns in a low-dimensional space.