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T Sne Script Generator

Examples

Iris Dataset

MNIST Dataset

Wine Dataset

Breast Cancer Dataset

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How to get started

Step 1

Enter the details of your dataset, features, perplexity, and learning rate using our intuitive form.

Step 2

Click on 'Generate Script' to create a custom Python script using t-SNE for your data visualization needs.

Step 3

Download and run the generated script to visualize your data effortlessly.

Main Features

TSNE Variants

Our T Sne Script Generator supports various t-SNE variants including t-sne, t sne, tsne, t-distributed stochastic neighbor embedding, and t-stochastic neighbor embedding to suit your specific data visualization needs.

TSNE Visualization

Experience seamless tsne visualization with our tool. Easily create tsne visualizer scripts that are well-commented and user-friendly.

TSNE Data Visualization

Start visualizing data using t sne with our generator. Whether you're visualizing data using t-sne for the first time or looking to streamline your workflow, our tool has you covered.

FAQ

What is t-SNE?

t-SNE (t-distributed stochastic neighbor embedding) is a machine learning algorithm for dimensionality reduction, particularly well-suited for the visualization of high-dimensional datasets.

How do I choose the perplexity value?

The perplexity value is a parameter that affects the balance between local and global aspects of your data. Common values range from 5 to 50. Experimenting with different values can help you find the best visualization for your dataset.

Can I use t-SNE for large datasets?

While t-SNE is powerful, it can be computationally intensive for very large datasets. For such cases, consider using optimized implementations or dimensionality reduction techniques before applying t-SNE.