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MMD-Assignment #1: Local Sensitive Hashing (LSH) for Item Search and Genre Classification for FMA dataset.

Team: Emin Guliev, Justus Rass & Christian Wiskott.

Requirements

  • Python 3
  • Numpy
  • Matplotlib
  • Jupyter

Cloning

Github repo can be cloned from:

https://github.com/ezorrio/genre-classification.git

If you have data files fetched from original source, clone using following command:

GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/ezorrio/genre-classification

Description

The 4 Python files should be placed in a directory with the .csv files in a folder called 'metadata'.

  • FMA.py
  • LSH.py
  • main.py
  • MusicSearch.py
  • metadata/
    • features.csv
    • tracks.csv
  • experiments/
  • paper/ - contains LaTeX source files for paper

To run it with the hyperparameters used for the final results, simply execute the 'experiments_manual.ipynb' file located in the experiments folder.

The experiments folder contains the ipython notebooks used to carry out the tests for validation. The experiments/results folder contains the raw results for the test suite used for k=3, 5, 7 nearest neighbours, as well as a condensed list of the best achieved results and the manual tests carried out with those parameters.