Metrics

Rating

Mean Absolute Error (MAE)

class cornac.metrics.MAE

Mean Absolute Error.

name

Name of the measure.

Type:string, value: ‘MAE’

Mean Squared Error (MSE)

class cornac.metrics.MSE

Mean Squared Error.

name

Name of the measure.

Type:string, value: ‘MSE’

Root Mean Squared Error (RMSE)

class cornac.metrics.RMSE

Root Mean Squared Error.

name

Name of the measure.

Type:string, value: ‘RMSE’

Ranking

Area Under the Curve (AUC)

class cornac.metrics.AUC

Area Under the ROC Curve (AUC).

References

https://arxiv.org/ftp/arxiv/papers/1205/1205.2618.pdf

Fmeasure (F1)

class cornac.metrics.FMeasure(k=-1)

F-measure@K@.

Parameters:k (int, optional, default: -1 (all)) – The number of items in the top@k list. If None, all items will be considered.

Mean Reciprocal Rank (MRR)

class cornac.metrics.MRR

Mean Reciprocal Rank.

Parameters:k (int, optional, default: -1 (all)) – The number of items in the top@k list. If None, all items will be considered.

References

https://en.wikipedia.org/wiki/Mean_reciprocal_rank

Normalized Cumulative Reciprocal Rank (NCRR)

class cornac.metrics.NCRR(k=-1)

Normalized Cumulative Reciprocal Rank.

Parameters:k (int, optional, default: -1 (all)) – The number of items in the top@k list. If None, all items will be considered.

Normalized Discount Cumulative Gain (NDCG)

class cornac.metrics.NDCG(k=-1)

Normalized Discount Cumulative Gain.

Parameters:k (int, optional, default: -1 (all)) – The number of items in the top@k list. If None, all items will be considered.

References

https://en.wikipedia.org/wiki/Discounted_cumulative_gain

Precision

class cornac.metrics.Precision(k=-1)

Precision@K.

Parameters:k (int, optional, default: -1 (all)) – The number of items in the top@k list. If None, all items will be considered.

Recall

class cornac.metrics.Recall(k=-1)

Recall@K.

Parameters:k (int, optional, default: -1 (all)) – The number of items in the top@k list. If None, all items will be considered.