accuracy module¶
The surprise.accuracy
module provides tools for computing accuracy
metrics on a set of predictions.
Available accuracy metrics:
Compute RMSE (Root Mean Squared Error). 

Compute MSE (Mean Squared Error). 

Compute MAE (Mean Absolute Error). 

Compute FCP (Fraction of Concordant Pairs). 
 surprise.accuracy.fcp(predictions, verbose=True)[source]¶
Compute FCP (Fraction of Concordant Pairs).
Computed as described in paper Collaborative Filtering on Ordinal User Feedback by Koren and Sill, section 5.2.
 Parameters
predictions (
list
ofPrediction
) – A list of predictions, as returned by thetest()
method.verbose – If True, will print computed value. Default is
True
.
 Returns
The Fraction of Concordant Pairs.
 Raises
ValueError – When
predictions
is empty.
 surprise.accuracy.mae(predictions, verbose=True)[source]¶
Compute MAE (Mean Absolute Error).
\[\text{MAE} = \frac{1}{\hat{R}} \sum_{\hat{r}_{ui} \in \hat{R}}r_{ui}  \hat{r}_{ui}\] Parameters
predictions (
list
ofPrediction
) – A list of predictions, as returned by thetest()
method.verbose – If True, will print computed value. Default is
True
.
 Returns
The Mean Absolute Error of predictions.
 Raises
ValueError – When
predictions
is empty.
 surprise.accuracy.mse(predictions, verbose=True)[source]¶
Compute MSE (Mean Squared Error).
\[\text{MSE} = \frac{1}{\hat{R}} \sum_{\hat{r}_{ui} \in \hat{R}}(r_{ui}  \hat{r}_{ui})^2.\] Parameters
predictions (
list
ofPrediction
) – A list of predictions, as returned by thetest()
method.verbose – If True, will print computed value. Default is
True
.
 Returns
The Mean Squared Error of predictions.
 Raises
ValueError – When
predictions
is empty.
 surprise.accuracy.rmse(predictions, verbose=True)[source]¶
Compute RMSE (Root Mean Squared Error).
\[\text{RMSE} = \sqrt{\frac{1}{\hat{R}} \sum_{\hat{r}_{ui} \in \hat{R}}(r_{ui}  \hat{r}_{ui})^2}.\] Parameters
predictions (
list
ofPrediction
) – A list of predictions, as returned by thetest()
method.verbose – If True, will print computed value. Default is
True
.
 Returns
The Root Mean Squared Error of predictions.
 Raises
ValueError – When
predictions
is empty.