dataset_loaders.yaml

#Default Loaders

'Netflix 10k':
  FullData:

    dataset:
      path: ./data/datasets/MovieLens 100k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    splitting:
      strategy: global
      train_size: 0.8
      test_consumes: 5

    validation:
      validation_size: 0.2

'Yelp Philadelphia':
  FullData:

    dataset:
      path: ./data/datasets/Yelp Philadelphia/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    splitting:
      # strategy: temporal
      strategy: user_history
      train_size: 0.8
      test_consumes: 5

    validation:
      validation_size: 0.2


'Yelp POI New Orleans':
  FullData:

    dataset:
      path: ./data/datasets/Yelp POI New Orleans/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    splitting:
      # strategy: temporal
      strategy: user_history
      train_size: 0.8
      test_consumes: 5

    validation:
      validation_size: 0.2


'Yelp POI Nashville':
  FullData:

    dataset:
      path: ./data/datasets/Yelp POI Nashville/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    splitting:
      # strategy: temporal
      strategy: user_history
      train_size: 0.8
      test_consumes: 5

    validation:
      validation_size: 0.2


'MovieLens 100k':
  FullData:

    dataset:
      path: ./data/datasets/MovieLens 100k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    # prefiltering:
    #   filter_users:
    #     min_consumption: 50
    #     num_users: 100
    #   filter_items: 
    #     min_ratings: 1
    #     num_items: 100

    splitting:
      strategy: user_history
      train_size: 0.8
      test_consumes: 5

    validation:
      validation_size: 0.2


'MovieLens 100k TrainTest':
  SplitData:

    dataset:
      train:
        path: ./data/datasets/MovieLens 100k TrainTest/train.data
        file_delimiter: "::"
        skip_head: false
      test:
        path: ./data/datasets/MovieLens 100k TrainTest/test.data
        file_delimiter: "::"
        skip_head: false

    # validation:
    #   x_validation: 
    #     path: ./data/datasets/MovieLens 100k TrainTest/x_validation.csv
    #     file_delimiter: "::"
    #     skip_head: false
    #   y_validation: 
    #     path: ./data/datasets/MovieLens 100k TrainTest/y_validation.csv
    #     file_delimiter: "::"
    #     skip_head: false


'Nano Dataset':
  FullData:
    
    dataset:
      path: ./data/datasets/Nano Dataset/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 1

    validation:
      validation_size: 0.2


"MovieLens 1M":
  FullData:

    dataset:
      path: ./data/datasets/MovieLens 1M/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    # prefiltering:
    #   filter_users:
    #     min_consumption: 50
    #     num_users: 100
    #   filter_items: 
    #     min_ratings: 1
    #     num_items: 100

    splitting:
      strategy: global
      train_size: 0.8
      test_consumes: 5

    # validation:
    #   validation_size: 0.2

"MovieLens 10M":
  FullData:
    
    dataset:
      path: ./data/datasets/MovieLens 10M/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"MovieLens 20M":
  FullData:
    
    dataset:
      path: ./data/datasets/MovieLens 20M/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"LastFM 5k":
  FullData:
    
    dataset:
      path: ./data/datasets/LastFM 5k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Kindle Store":
  FullData:
    
    dataset:
      path: ./data/datasets/Kindle Store/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Kindle 4k":
  FullData:
    dataset:
      path: ./data/datasets/Kindle 4k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Netflix":
  FullData:
    dataset:
      path: ./data/datasets/Netflix/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
      
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Netflix 10k":
  FullData:

    dataset:
      path: ./data/datasets/Netflix 10k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Good Books":
  FullData:
    dataset:
      path: ./data/datasets/Good Books/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Yahoo Music":
  FullData:
    
    dataset:
      path: ./data/datasets/Yahoo Music/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

"Good Reads 10k":
  FullData:    
    
    dataset:
      path: ./data/datasets/Good Reads 10k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

'Yahoo Music 5k':
  FullData:
    dataset:
      path: ./data/datasets/Yahoo Music 5k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2

'Yahoo Music 10k':
   FullData:

    dataset:
      path: ./data/datasets/Yahoo Music 10k/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true

    # prefiltering:
    #   filter_users:
    #     min_consumption: 50
    #     num_users: 100
    #   filter_items: 
    #     min_ratings: 1
    #     num_items: 100

    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5

    # validation:
      # validation_size: 0.2

    
'MovieLens 25M':
  FullData:
    
    dataset:
      path: ./data/datasets/MovieLens 25M/ratings.csv
      random_seed: 0
      file_delimiter: ","
      skip_head: true
    
    splitting:
      strategy: temporal
      train_size: 0.8
      test_consumes: 5  

    validation:
      validation_size: 0.2