autointent.metrics.retrieval

Retrieval metrics.

Classes

RetrievalMetricFn

Protocol for retrieval metrics.

Functions

retrieval_map(query_labels, candidates_labels[, k])	Calculate the mean average precision at position k.
retrieval_map_intersecting(query_labels, candidates_labels)	Calculate the mean average precision at position k for the intersecting labels.
retrieval_map_macro(query_labels, candidates_labels[, k])	Calculate the mean average precision at position k for the intersecting labels.
retrieval_hit_rate(query_labels, candidates_labels[, k])	Calculate the hit rate at position k.
retrieval_hit_rate_intersecting(query_labels, ...[, k])	Calculate the hit rate at position k for the intersecting labels.
retrieval_hit_rate_macro(query_labels, candidates_labels)	Calculate the hit rate at position k for the intersecting labels.
retrieval_precision(query_labels, candidates_labels[, k])	Calculate the precision at position k.
retrieval_precision_intersecting(query_labels, ...[, k])	Calculate the precision at position k for the intersecting labels.
retrieval_precision_macro(query_labels, candidates_labels)	Calculate the precision at position k for the intersecting labels.
retrieval_ndcg(query_labels, candidates_labels[, k])	Calculate the Normalized Discounted Cumulative Gain (NDCG) at position k.
retrieval_ndcg_intersecting(query_labels, ...[, k])	Calculate the Normalized Discounted Cumulative Gain (NDCG) at position k for the intersecting labels.
retrieval_ndcg_macro(query_labels, candidates_labels)	Calculate the Normalized Discounted Cumulative Gain (NDCG) at position k for the intersecting labels.
retrieval_mrr(query_labels, candidates_labels[, k])	Calculate the Mean Reciprocal Rank (MRR) at position k.
retrieval_mrr_intersecting(query_labels, candidates_labels)	Calculate the Mean Reciprocal Rank (MRR) at position k for the intersecting labels.
retrieval_mrr_macro(query_labels, candidates_labels[, k])	Calculate the Mean Reciprocal Rank (MRR) at position k for the intersecting labels.