THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS¶
Why this mattered¶
TBD
Abstract¶
The articles published by the Annals of Eugenics (1925–1954) have been made available online as an historical archive intended for scholarly use. The work of eugenicists was often pervaded by prejudice against racial, ethnic and disabled groups. The online publication of this material for scholarly research purposes is not an endorsement of those views nor a promotion of eugenics in any way.
Related¶
- enables → Support-Vector Networks — Fisher's discriminant analysis framed classification as separating measured classes, a statistical precursor to support-vector decision boundaries.
- enables → Particle swarm optimization — Fisher's discriminant analysis introduced population-separating optimization ideas later echoed in swarm-based search over continuous objective functions.
- enables → Particle swarm optimization — Fisher's discriminant analysis introduced optimization over multivariate measurements, enabling later population-based search methods such as particle swarm optimization.
- enables → A new optimizer using particle swarm theory — Fisher's discriminant analysis introduced multivariate optimization over measured features, a statistical foundation later echoed in population-based search methods like particle swarm optimization.
- cite ← Support-Vector Networks — Support-vector networks cite Fisher's discriminant analysis as an earlier statistical approach to supervised classification from multiple measurements.
- cite ← Particle swarm optimization — Particle swarm optimization cites Fisher's discriminant-analysis work as an early statistical method for separating populations using multiple measured variables.
- cite ← Particle swarm optimization — Particle swarm optimization cites Fisher's discriminant analysis paper as an early statistical method for classification from multiple measurements.
- cite ← A new optimizer using particle swarm theory — Particle swarm optimization cites Fisher's iris measurement paper as a benchmark classification dataset for evaluating the optimizer's search performance.