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CS-433 Project 1

File description:

  • helpers.py is the file provided for us
  • Data Prepocessing.ipynb is the code to preprocess the raw data
  • basic_funtions includes codes contributing to logistic regression
  • logistic_regression is our applied method
  • _sub.csv is the predictions we used to get our best score (0.388 f1 score and 0.863 accuracy)
  • notebook.ipynb is a notebook we used to train, test and tune all parameters, and test different strategies
  • implementations.py includes all applied functions
  • run.py is the script that generates our best attempt file
  • Report.pdf is our final report file.

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  • Jupyter Notebook 97.2%
  • Python 2.8%