elliot.evaluation.metrics.novelty.EPC package¶

Submodules¶

elliot.evaluation.metrics.novelty.EPC.epc module¶

This is the implementation of the Expected Popularity Complement metric. It proceeds from a user-wise computation, and average the values over the users.

class elliot.evaluation.metrics.novelty.EPC.epc.EPC(recommendations, config, params, eval_objects)[source]¶

Bases: elliot.evaluation.metrics.base_metric.BaseMetric

Expected Popularity Complement (EPC)

This class represents the implementation of the Expected Popularity Complement recommendation metric.

For further details, please refer to the paper

Note

EPC can be read as the expected number of seen relevant recommended items not previously seen

\[\mathrm{EPC}=C \sum_{i_{k} \in R} \operatorname{disc}(k) p\left(r e l \mid i_{k}, u\right)\left(1-p\left(\operatorname{seen} \mid t_{k}\right)\right)\]

To compute the metric, add it to the config file adopting the following pattern:

simple_metrics: [EPC]

eval_user_metric()[source]¶: Evaluation function :return: the overall averaged value of Expected Popularity Complement per user

static name()[source]¶: Metric Name Getter :return: returns the public name of the metric

elliot.evaluation.metrics.novelty.EPC.extended_epc module¶

This is the implementation of the Expected Popularity Complement metric. It proceeds from a user-wise computation, and average the values over the users.

class elliot.evaluation.metrics.novelty.EPC.extended_epc.ExtendedEPC(recommendations, config, params, eval_objects, additional_data)[source]¶

Bases: elliot.evaluation.metrics.base_metric.BaseMetric

Extended EPC

This class represents the implementation of the Extended EPC recommendation metric.