Error 0035
Updated: June 14, 2017
Error 0035
Exception occurs if no features were provided for a given user or item.
This error in Azure Machine Learning occurs you are trying to use a recommendation model for scoring but a feature vector cannot be found.
The Matchbox recommender has certain requirements that must be met when using either item features or user features. This error indicates that a feature vector is missing for a user or item that you provided as input. You must ensure that a vector of features is available in the data for each user or item.
For example, if you trained a recommendation model using features such as the user's age, location, or income, but now want to create scores for new users who were not seen during training, you must provide some equivalent set of features (namely, age, location and income values) for the new users in order to make appropriate predictions for them.
If you do not have any features for these users, consider feature engineering to generate appropriate features. For example, if you do not have individual user age or income values, you might generate approximate values to use for a group of users.
When you are scoring from a recommendation mode, you can use item or user features only if you previously used item or user features during training. For more information, see Score Matchbox Recommender.
For general information about how the Matchbox recommendation algorithm works, and how to prepare a dataset of item features or user features, see Train Matchbox Recommender.
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| Exception Messages |
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| No features were provided for a required user or item. |
| Features for {0} required but not provided. |
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