coremlcreateml

CreateML Recommender Training Error: Item IDs in the recommender model must be numbered 0, 1, ..., num_items - 1

I'm using CreateML to generate a Recommender model using an implicit dataset of the format: User ID, Item ID. The data is loaded into CreateML as a CSV with about 400k rows.

When attempting to 'Train' the model, I receive the following error: 

Training Error: Item IDs in the recommender model must be numbered 0, 1, ..., num_items - 1

My dataset is in the following format:

"user_id","item_id"
"e7ca1b039bca4f81a33b21acc202df24","f7267c60-6185-11ea-b8dd-0657986dc989"
"1cd4285b19424a94b33ad6637ec1abb2","e643af62-6185-11ea-9d27-0657986dc989"
"1cd4285b19424a94b33ad6637ec1abb2","f2fd13ce-6185-11ea-b210-0657986dc989"
"1cd4285b19424a94b33ad6637ec1abb2","e95864ae-6185-11ea-a254-0657986dc989"
"31042cbfd30c42feb693569c7a2d3f0a","e513a2dc-6185-11ea-9b4c-0657986dc989"
"39e95dbb21854534958d53a0df33cbf2","f27f62c6-6185-11ea-b14c-0657986dc989"
"5c26ca2918264a6bbcffc37de5079f6f","ec080d6c-6185-11ea-a6ca-0657986dc989"

I've tried modifying both Item ID and User ID to enumerated IDs, but I still receive the training error. Example:

"item_ids","user_ids"
0,0
1,0
2,0
2,0
0,225
400,225
409,225
0,282
0,4
8,4
8,4

I receive this error both within the CreateML UI and when using CreateML within a Swift playground. I've also tried removing duplicates and verified that the maximum ID for each column is (num_items - 1).

I've searched for documentation on what the exact requirement is for the set of IDs with no luck.

Thank you in advance for any helping clarifying this error message.

Solution

  • I was able to discuss this issue with Apple's CoreML developers during WWDC2020. They described this as a known bug which will be fixed with the upcoming OS (Big Sur). The work-around for this bug is:

    In the CSV dataset, create records for a single user which interacts with ALL items, and create records for a single item interacted with by ALL users.

    Using pandas in python, I essentially implemented the following:

    # Find the unique item ids
item_ids = ratings_df.item_id.unique()

# Find the unique user ids
user_ids = ratings_df.user_id.unique()

# Create a 'dummy user' which interacts with all items
mock_item_interactions_df = pd.DataFrame({'item_id': item_ids, 'user_id': 'mock-user'})
ratings_with_mocks_df = ratings_df.append(mock_item_interactions_df)

# Create a 'dummy item' which interacts with all users
mock_item_interactions_df = pd.DataFrame({'item_id': 'mock-item', 'user_id': user_ids})
ratings_with_mocks_df = ratings_with_mocks_df.append(mock_item_interactions_df)

# Export the CSV
ratings_with_mocks_df.to_csv('data/ratings-w-mocks.csv', quoting=csv.QUOTE_NONNUMERIC, index=True)

    Using this CSV, I successfully generated a CoreML model using CreateML.