_RecoDQMetric

class rectools.metrics.dq._RecoDQMetric(k: int, deep: bool = False)[source]

Recommendations data quality metric base class.

Warning: This class should not be used directly. Use derived classes instead.

Parameters

k (int) – Number of items at the top of recommendations list that will be used to calculate metric.
deep (bool, default False) – Whether to calculated detailed value of the metric for each user. Otherwise just the share of users with identified problems will be returned (this is the default behaviour).

Inherited-members

Methods

`calc`(reco)	Calculate metric value.
`calc_per_user`(reco)	Calculate metric values for all users.

Attributes

deep

calc(reco: DataFrame) → float[source]

Calculate metric value.

Parameters: reco (pd.DataFrame) – Recommendations table with columns Columns.User, Columns.Item, Columns.Rank.
Returns: Value of metric (average between users).
Return type: float

calc_per_user(reco: DataFrame) → Series[source]

Calculate metric values for all users.

Parameters: reco (pd.DataFrame) – Recommendations table with columns Columns.User, Columns.Item, Columns.Rank.
Returns: Values of metric (index - user id, values - metric value for every user).
Return type: pd.Series