EASE-ReD

CMPT 353 - E100 SPRING 2024 Final Project

An exploratory analysis to investigate the potential correlation between restaurant cuisine and the ethnic demographics of the local population.

Group

Name	Student Number	Git ID
Heorhii Shramko	301428235	ShayGeko
Eunsong Koh	301549157	eunsongkoh
Tianyu Liu	301249861	tla109

Prerequisties

To run this project, Python3 and the following libraries must be installed:

Installing Python3:

Download and install Python3 from the official website.

Installing Required Libraries:

• Pandas
• Numpy
• Pytorch
• Matplotlib
• Sentence_transformers
• Pyspark
• Tqdm
• Sklearn
• Dask
• shutil
• PyYaml

You can install the required Python libraries using pip, Python's package installer. Open a terminal or command prompt and execute the following commands:

pip3 install torch pandas numpy matplotlib pyyaml tqdm scikit-learn dask 

Run

Step 1. Clone the Repository

git clone [email protected]:ShayGeko/EASE-ReD.git

cd ProjectTourOSM

Step 2. (Optional) Generate Embeddings:

Gets the data from ./bingMaps/restaurantCategory/ and produce ./embeddings/pca_category_bing_embeddings.csv
and ./embeddingscategory_bing_embeddings.csv

python3 create_embeddings.py

Step 3. Train on the Embeddings

1. Go to configs/ce_pca_category.yml and increment the counter in the name
   e.g. name: 'ce-category-embedding-1' -> name: 'ce-category-embedding-2'

2. From the root directory:

python3 train.py configs/ce_pca_category.yml

will train with CrossEntropy loss on the PCA'd embeddings

If there was a problem with embedding generation (even though there shouldnt be 🙏), you can use the other embedding file for names instead of categories. Just change the config file in Step 3 from ce_pca_category.yml to ce_pca_name.yml

Then one can observe results in under experiments/<experiment name from config file>/ The predictions are stored every 1000 epochs under visuals/ and the loss is plotted iteratively in loss.png

Data Visualizations

From the root directory:
python3 visualize.py <experiment name from config file>

License

MIT © Heorhii Shramko