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.gitignore
LICENSE
cluster_events.py
dist.py
events_stats.py
fix.py
get_events.py
pos_stats.py
predict_sold_out.py
purchase_pos.py
readme.txt
requirements.txt
segment.py
test.py
test2.py
ticket_purchases.py

readme.txt

Code for DT8109 Business Systems Case Study 2017
================================================

Code used for the case study in DT8109 Business Systems at NTNU.

Basically does four things:

1. Gathers a lot of data about the dataset (events_stats.py)
2. Performs a hierarcical clustering (cluster_events.py)
3. Performs a classification using naive bayes (segment.py)
4. Performs an analysis of when an event breaks even using tree induction (predict_sold_out.py)


dist.py contains helper funtions for calculating distances, and get_events.py contains utilities for reading data.