Tste.py File

Most versions of this script on GitHub (like the gcr/tste-theano repository ) are built using older libraries. : You usually need numpy and theano .

The tste.py script generally expects an input file of . Each line in your data should represent one "A is closer to B than to C" relationship. 1. Format Your Input tste.py

: If the embedding looks like a random "ball," try lowering the learning rate. 📊 When to use t-STE vs. t-SNE Learning to Taste A Multimodal Wine Dataset Most versions of this script on GitHub (like

(Alpha) : Degrees of freedom for the Student-t distribution (usually set to is dimensions). Each line in your data should represent one

python tste.py --triplets triplets.txt --n_objects 100 --n_dims 2 Use code with caution. Copied to clipboard 3. Key Parameters to Tune

Your input file (e.g., triplets.txt ) should contain zero-indexed integer IDs: 0 1 2 5 3 8 2 0 4 Use code with caution. Copied to clipboard (Meaning: Object 0 is more like Object 1 than Object 2) 2. Run the Embedding

Note : Theano is largely discontinued; you may need to use a newer fork like PyTensor or find a Cython-optimized version . : pip install numpy theano Use code with caution. Copied to clipboard 📝 How to Use the Script