Class RankingMetrics (3.4.0)

Version 3.4.0

• 3.27.0 (latest)
• 3.26.0
• 3.25.0
• 3.24.0
• 3.23.1
• 3.22.0
• 3.21.0
• 3.20.1
• 3.19.0
• 3.18.0
• 3.17.2
• 3.16.0
• 3.15.0
• 3.14.1
• 3.13.0
• 3.12.0
• 3.11.4
• 3.4.0
• 3.3.6
• 3.2.0
• 3.1.0
• 3.0.1
• 2.34.4
• 2.33.0
• 2.32.0
• 2.31.0
• 2.30.1
• 2.29.0
• 2.28.1
• 2.27.1
• 2.26.0
• 2.25.2
• 2.24.1
• 2.23.3
• 2.22.1
• 2.21.0
• 2.20.0
• 2.19.0
• 2.18.0
• 2.17.0
• 2.16.1
• 2.15.0
• 2.14.0
• 2.13.1
• 2.12.0
• 2.11.0
• 2.10.0
• 2.9.0
• 2.8.0
• 2.7.0
• 2.6.2
• 2.5.0
• 2.4.0
• 2.3.1
• 2.2.0
• 2.1.0
• 2.0.0
• 1.28.2
• 1.27.2
• 1.26.1
• 1.25.0
• 1.24.0
• 1.23.1
• 1.22.0
• 1.21.0
• 1.20.0
• 1.19.0
• 1.18.0
• 1.17.0
• 1.16.0

RankingMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.

Attributes
Name	Description
mean_average_precision	google.protobuf.wrappers_pb2.DoubleValue Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
mean_squared_error	google.protobuf.wrappers_pb2.DoubleValue Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
normalized_discounted_cumulative_gain	google.protobuf.wrappers_pb2.DoubleValue A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
average_rank	google.protobuf.wrappers_pb2.DoubleValue Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.

Inheritance

builtins.object > proto.message.Message > RankingMetrics

Methods

__delattr__

__delattr__(key)

Delete the value on the given field.

This is generally equivalent to setting a falsy value.

__eq__

__eq__(other)

Return True if the messages are equal, False otherwise.

__ne__

__ne__(other)

Return True if the messages are unequal, False otherwise.

__setattr__

__setattr__(key, value)

Set the value on the given field.

For well-known protocol buffer types which are marshalled, either the protocol buffer object or the Python equivalent is accepted.