The second question of 2023 MCM-ICM Problem C
├── data
│ ├── df.xlsx # processed data after run features.py
│ ├── Problem_C_Data_Wordle.xlsx # raw data
│ ├── unigram_freq.csv # download from https://www.kaggle.com/datasets/rtatman/english-word-frequency
│ └── words.json # raw words
├── 2.py # train & pred
├── features.py # extract 6 features
├── find.py # return features
├── requirements.txt
└── tries.py # normal distribution curve fit, convert 7 percent features into 2 featuresconda create --name hanlp python=3.8
conda activate hanlp
pip install -r requirements.txt
python features.py # features.py use tensorflow
python tries.py
conda deactivate
python 2.py # 2.py use torch