160 citations · 162 across the 3 of their papers we have counts for
3 papers · 1 filter
Estimating Multi-label Accuracy using Labelset Distributions
Laurence A. F. Park, Jesse Read
A multi-label classifier estimates the binary label state (relevant vs irrelevant) for each of a set of concept labels, for any given instance. Probabilistic multi-label classifier…
River: machine learning for streaming data in Python
Jacob Montiel, Max Halford, Saulo Martiello Mastelini +8
River is a machine learning library for dynamic data streams and continual learning. It provides multiple state-of-the-art learning methods, data generators/transformers, performan…
Classifier Chains: A Review and Perspectives
Jesse Read, Bernhard Pfahringer, Geoff Holmes +1
The family of methods collectively known as classifier chains has become a popular approach to multi-label learning problems. This approach involves linking together off-the-shelf…