elliot.evaluation.metrics.rating.rmse package¶
Submodules¶
elliot.evaluation.metrics.rating.rmse.rmse module¶
This is the implementation of the Root Mean Squared Error metric. It proceeds from a user-wise computation, and average the values over the users.
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class
elliot.evaluation.metrics.rating.rmse.rmse.RMSE(recommendations, config, params, eval_objects)[source]¶ Bases:
elliot.evaluation.metrics.base_metric.BaseMetricRoot Mean Squared Error
This class represents the implementation of the Root Mean Squared Error recommendation metric.
For further details, please refer to the link
\[\mathrm{RMSE} = \sqrt{\frac{1}{|{T}|} \sum_{(u, i) \in {T}}(\hat{r}_{u i}-r_{u i})^{2}}\]\(T\) is the test set, \(\hat{r}_{u i}\) is the score predicted by the model
\(r_{u i}\) the actual score of the test set.
To compute the metric, add it to the config file adopting the following pattern:
simple_metrics: [RMSE]