methodology-9
Core set discovery
3260 papers • 126 benchmarks • 313 datasets
A core set in machine learning is defined as the minimal set of training samples that allows a supervised algorithm to deliver a result as good as the one obtained when the whole set is used.
(Image credit: Papersgraph)
Benchmarks
These leaderboards are used to track progress in core-set-discovery-9
Trend
Dataset
Best Model
Actions
micro-mass
micro-mass
Soybean
Soybean
Credit-g
Credit-g
Libraries
iUse these libraries to find core-set-discovery-9 models and implementations
Datasets
Subtasks
No subtasks available.
Most implemented papers
Uncovering Coresets for Classification With Multi-Objective Evolutionary Algorithms
Pietro Barbiero, Giovanni Squillero, A. Tonda•Wed Feb 19 2020
A novel approach is presented: candidate corsets are iteratively optimized, adding and removing samples, and a multi-objective evolutionary algorithm is used to minimize simultaneously the number of points in the set and the classification error.
4
