Python API

Models

models.PLT(output[, tree_type, arity, …])

Probabilistic Labels Trees (PLTs) model with linear node estimators, using CPP core.

models.HSM(output[, tree_type, arity, …])

Hierarchical Softmax model with linear node estimators, using CPP core.

models.BR(output[, hash, …])

Binary Relevance model with linear node estimators, using CPP core

models.OVR(output[, hash, …])

One Versus Rest model with linear node estimators, using CPP core.

Datasets

datasets.load_dataset(dataset[, subset, …])

Downloads the dataset from the internet and puts it in root directory.

Measures

measures.precision_at_k(Y_true, Y_pred[, k])

Calculate precision at k

measures.recall_at_k(Y_true, Y_pred[, k])

Calculate recall at k

measures.coverage_at_k(Y_true, Y_pred[, k])

Calculate coverage at k

measures.dcg_at_k(Y_true, Y_pred[, k])

Calculate DCG at k

measures.ndcg_at_k(Y_true, Y_pred[, k])

Calculate nDCG at k

measures.hamming_loss(Y_true, Y_pred)

Calculate hamming loss