zhugejun / student-dropouts-prediction

End-to-end dropout prediction

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End-to-End Student Dropouts Prediction

Features

Demographics

  • Age
  • Gender
  • Ethnicity

Academic

  • Full time status
  • First generation
  • Number of credits is attemtping
  • Number of courses retaken
  • New student or not
  • Number of developmental math courses
  • Number of developmental english courses
  • Course modularity
  • Past dropout rate
  • Dropout history for the last 3 semesters
  • High school GPA if a student is new to college
  • Last cumulative GPA
  • Average precentage of absences
  • TODO: data from Canvas

Data

Get Raw Data

Simply run the following command:

mlflow run ./src/data/get_data/

The data will be saved in data/raw/ folder.

Preprocess Data

To get the preprocessed data for week 10, simply run the following command:

mlflow run ./src/preprocess/ -P week_number=10

The preprocessed data named cleaned-10.csv will be saved in data/processed/ folder.

Model

  • Decision Tree
  • Gradient Boosting Decision Tree

About

End-to-end dropout prediction

License:MIT License


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