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reproduce_results.sh
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#!/usr/bin/env bash
# This script reproduces the results reported in Table 2, Figure 7a, Table 6
# and Table 12 of our paper
# Vall et al. "Feature-Combination Hybrid Recommender Systems for Automated
# Music Playlist Continuation." User Modeling and User-Adapted Interaction,
# 2019 (in press).
# It should also serve as a guide to get familiar with the code, reproduce the
# rest of the results, and even conduct additional experiments.
# switch to the Python virtual environment
source venv/bin/activate
# create directory to output the results
mkdir -p results
# Profiles (run on gpu if possible)
python profiles_weak.py --model models/profiles/audio2cf_tags_logs.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python profiles_weak.py --model models/profiles/audio2cf_tags_logs.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/profiles_audio2cf_tags_logs
python profiles_weak.py --model models/profiles/logs.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python profiles_weak.py --model models/profiles/logs.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/profiles_logs
python profiles_weak.py --model models/profiles/audio2cf.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python profiles_weak.py --model models/profiles/audio2cf.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/profiles_audio2cf
# Membership (run on gpu if possible)
python membership_weak.py --model models/membership/audio2cf_tags_logs.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python membership_weak.py --model models/membership/audio2cf_tags_logs.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/membership_audio2cf_tags_logs
python membership_weak.py --model models/membership/logs.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python membership_weak.py --model models/membership/logs.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/membership_logs
python membership_weak.py --model models/membership/audio2cf.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python membership_weak.py --model models/membership/audio2cf.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/membership_audio2cf
# MF
python mf_weak.py --model models/mf/wmf.py --dataset data/aotm/ --msd data/MSD/ --fit --seed 1
python mf_weak.py --model models/mf/wmf.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --seed 1 > results/mf
# Hybrid MF
python mf_weak.py --model models/mf/wmf.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --precomputed logs --seed 1 > results/hmf_logs
python mf_weak.py --model models/mf/wmf.py --dataset data/aotm/ --msd data/MSD/ --test --song_occ 0 1 2 3 4 5 --precomputed audio2cf --seed 1 > results/hmf_audio2cf
# Neighbors
python neighbors_weak.py --user --dataset data/aotm/ --msd data/MSD/ --song_occ 0 1 2 3 4 5 > results/neighbors
# Artists
python neighbors_weak.py --artist --dataset data/aotm/ --msd data/MSD/ --song_occ 0 1 2 3 4 5 > results/artists
# CAGH
python neighbors_weak.py --artist --pop --dataset data/aotm/ --msd data/MSD/ --song_occ 0 1 2 3 4 5 > results/cagh
# Popularity
python popularity_weak.py --dataset data/aotm/ --msd data/MSD/ --song_occ 0 1 2 3 4 5 > results/popularity
# Random
python popularity_weak.py --dataset data/aotm/ --msd data/MSD/ --random --song_occ 0 1 2 3 4 5 > results/random
# turn off Python virtual environment
deactivate