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.
T Sne Script Generator
Examples
Iris Dataset
MNIST Dataset
Wine Dataset
Breast Cancer Dataset
Examples
Iris Dataset
MNIST Dataset
Wine Dataset
Breast Cancer Dataset
Instant generations
Infinite revisions
Thousands of services
Trusted by millions
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 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.