tfrs.examples.movielens.evaluate
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Evaluates a Movielens model on the supplied datasets.
tfrs.examples.movielens.evaluate(
user_model: tf.keras.Model,
movie_model: tf.keras.Model,
test: tf.data.Dataset,
movies: tf.data.Dataset,
train: Optional[tf.data.Dataset] = None,
k: int = 10
) -> Dict[Text, float]
Args |
user_model
|
User representation model.
|
movie_model
|
Movie representation model.
|
test
|
Test dataset.
|
movies
|
Dataset of movies.
|
train
|
Training dataset. If supplied, recommendations for training watches
will be removed.
|
k
|
The cutoff value at which to compute precision and recall.
|
Returns |
Dictionary of metrics.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[]]