Fin2Vec

Prerequisites

install conda

• create a new conda environment named hoynet with environment.yml
• PyTorch is essential. Set PyTorch according to your own local environment

$ conda env create -f environment.yml

activate the conda environment

$ conda activate hoynet

deactivate the conda enviroment when finished the jobs

$ conda deactivate

Training

• check configuration(.yml) carefully and customize it
• sample configurations(.yml) are in demo/training directory
• Caution! Ensure the configuration is well-written to recognize the device capabilities and prevent forced shutdowns
• 주의! 기기 성능에 맞게 실행 구성을 작성하시오.
• priceFile and codeFile is from crawling

PCRN training (logging)

$ python ./pcrn.py -c ./demo/training/pcrn.yml >> log.txt

Fin2Vec training (logging)

$ python ./fin2vec.py -c ./demo/training/fin2vec.yml >> log.txt

Demo

• check configuration(.yml) carefully and customize it
• sample configurations(.yml) are in demo/inference or demo/wordClustering directory
• Caution! Ensure the configuration is well-written to recognize the device capabilities and prevent forced shutdowns
• 주의! 기기 성능에 맞게 실행 구성을 작성하시오.

Fin2Vec Inference

$ python ./inference.py -c ./demo/inference/inference.yml

Clustering with Word Embedding

$ python ./wordClustering.py -c ./demo/wordClustering/wordClustering.yml

Visualize

Visualize Loss

$ python visualize/lossVisualize.py -f log.txt -i Title -l True