elliot.evaluation.metrics.bias.aclt package

Submodules

elliot.evaluation.metrics.bias.aclt.aclt module

This is the implementation of the Average coverage of long tail items metric. It proceeds from a user-wise computation, and average the values over the users.

class elliot.evaluation.metrics.bias.aclt.aclt.ACLT(recommendations, config, params, eval_objects)

Bases: elliot.evaluation.metrics.base_metric.BaseMetric

Average coverage of long tail items

This class represents the implementation of the Average coverage of long tail items recommendation metric.

For further details, please refer to the paper

\[\mathrm {ACLT}=\frac{1}{\left|U_{t}\right|} \sum_{u \in U_{f}} \sum_{i \in L_{u}} 1(i \in \Gamma)\]

\(U_{t}\) is the number of users in the test set.

\(L_{u}\) is the recommended list of items for user u.

\(1(i \in \Gamma)\) is an indicator function and it equals to 1 when i is in Gamma.

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

simple_metrics: [ACLT]

eval_user_metric()

Evaluation function :return: the overall averaged value of ACLT

static name()

Metric Name Getter :return: returns the public name of the metric

Module contents