d4r3topk / Data-Mining---CSE-572-project

Data-Mining-CSE-572-project

Phase 2

• The final features set which we have considered have following features,

  • CGM velocity
  • Moving RMS velocity
  • Discrete Wavelet Transform
  • Fast Fourier Transform

• After comparing the validation set accuracies of individual models, we have finalized the following models

  • RandomForest
  • AdaBoost
  • XGBoost
  • Naive Bayes

• Individual Contributions

  • RandomForest -> Surya Vamsi Tenneti
  • AdaBoost -> Santhosh Kumar
  • XGBoost -> Sai Uttej Thunuguntla
  • Naive Bayes -> Aryan Prasad

Steps to execute

• Run the Assignment2.py and after running, it asks for a test file name

> python Assignment2.py
Please enter the test file name: 

• After running, 4 output files with the predictions from each model is generated with the following names,
  • RForest_output.csv
  • XGBoost_output.csv
  • Adaboost_output.csv
  • NaiveBayes_output.csv

System specifications

• System should have Python 3+ (64-bit)
• The following libraries need to be installed
  • Numpy
  • Pandas
  • XGBoost
  • Scikit-learn
  • Pickle
  • pywt