recpack.algorithms.loss_functions.bpr_loss_wrapper
- recpack.algorithms.loss_functions.bpr_loss_wrapper(X_true: scipy.sparse._csr.csr_matrix, X_pred: scipy.sparse._csr.csr_matrix, batch_size=1000, sample_size=None, exact=False)
Wrapper around
bpr_loss()
function for use withrecpack.algorithms.stopping_criterion.StoppingCriterion
.Positive and negative items are sampled using
recpack.algorithms.samplers.BootstrapSampler
. Scores are then extracted from the X_pred, and these positive and negative predictions are passed to thebpr_loss()
function.- Parameters
X_true (csr_matrix) – The expected interactions for the users
X_pred (csr_matrix) – The predicted scores for users
batch_size (int, optional) – size of the batches to sample, defaults to 1000
sample_size (int, optional) – How many samples to construct
exact (bool, optional) – If True sampling happens exact, otherwise sampling assumes high sparsity of data, accepting a minimal amount of false negatives, speeding up sampling without loss of quality, defaults to False
- Returns
The mean of the losses of sampled pairs
- Return type
float