https://github.com/voschezang/project-data-mining

Predict which hotels users are most likely to book
https://github.com/voschezang/project-data-mining

analytics data-science

Last synced: 6 days ago
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Predict which hotels users are most likely to book

• Host: GitHub
• URL: https://github.com/voschezang/project-data-mining
• Owner: voschezang
• License: mit
• Created: 2019-04-01T16:14:58.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2019-05-24T19:56:11.000Z (about 7 years ago)
• Last Synced: 2025-02-24T00:24:53.764Z (over 1 year ago)
• Topics: analytics, data-science
• Language: Jupyter Notebook
• Homepage:
• Size: 2.9 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Assignment 1

(this branch)[https://github.com/voschezang/Data-Mining/tree/A1]

# Assignment 2

Preprocess data with `clean_data.py` (fit + transform train/test data). Further process data with `clean_data_2*.py` (clustering and SVD).

The notebooks `A2-***.ipynb` show how to crossvalidata machine learning models and generate result-files. They should be self-explanatory.

Kaggle Expedia hotel recommedation challenge ([link](https://www.kaggle.com/c/vu-dmt-2assignment/))

Performance is measured using [Normalized Discounted Cumulative Gain (NDCG)@5](http://dalelane.co.uk/blog/?p=3403) (see also (https://en.wikipedia.org/wiki/Discounted_cumulative_gain)