A project to learn about data cleaning, data visualisation, logistic regression and multiclass classification by recreating Poulard's Sorting Hat from Harry Potter, i.e. using the One VS Rest strategy with Logistic Regression to classify Hogwarts students using academic data.
Dependencies listed in requirements.txt
git clone https://github.com/LaiAnTan/42KL-dslrpip install -r requirements.txtor in other environments such as conda
Datasets can be found in the datasets directory.
Data Analysis:
python3 srcs/describe.py <dataset_train / dataset_test> prints a statistical report onto the terminal.
Data Visualisation:
python3 srcs/histogram.py saves a histogram to graphs directory.
python3 srcs/scatter_plot.py saves a scatter plot to graphs directory.
python3 srcs/pair_plot.py saves a pair plot to graphs directory.
ML Model:
python3 srcs/logreg_train.py <dataset_train> trains the model and saves the model details to models directory.
python3 srcs/logreg_plot.py <dataset_test> loads the model and generates a file with predictions, dataset_prediction.csv to datasets directory.
Notes written in notes.md.