Search

Searching

• Release Highlights for scikit-learn 1.5

  ...[ 0.1, 1.3, 1.1], [-0.1, -1.4, -1.4], [-4.9, 1.5, -1.5], [ 0.1, 1.6, 1.6]]) Pairwise distances with non-numeric arrays pairwise_distances can now compute distances between non-numeric arrays using a callab...

• Robust covariance estimation and Mahalanobis distances relevance
• sklearn.metrics
• sklearn.metrics.DistanceMetric (Python class, in DistanceMetric)
• sklearn.metrics.pairwise.cosine_distances (Python function, in cosine_distances)
• sklearn.metrics.pairwise.distance_metrics (Python function, in distance_metrics)
• sklearn.metrics.pairwise.euclidean_distances (Python function, in euclidean_distances)
• sklearn.metrics.pairwise.haversine_distances (Python function, in haversine_distances)
• sklearn.metrics.pairwise.manhattan_distances (Python function, in manhattan_distances)
• sklearn.metrics.pairwise.nan_euclidean_distances (Python function, in nan_euclidean_distances)
• sklearn.metrics.pairwise.paired_cosine_distances (Python function, in paired_cosine_distances)
• sklearn.metrics.pairwise.paired_distances (Python function, in paired_distances)
• sklearn.metrics.pairwise.paired_euclidean_distances (Python function, in paired_euclidean_distances)
• sklearn.metrics.pairwise.paired_manhattan_distances (Python function, in paired_manhattan_distances)
• sklearn.metrics.pairwise_distances (Python function, in pairwise_distances)
• sklearn.metrics.pairwise_distances_argmin (Python function, in pairwise_distances_argmin)