Evolving accuracy: A genetic algorithm to improve election night forecasts
Election night forecasting depends on finding homogenous groups of polling stations. The industry standard relies on human intuition and K-means clustering. We propose a genetic algorithm to find grouping solutions. Our method outperforms human groupings by far. The concepts are demonstrated with local Austrian election data from 2010.
genetic algorithm election night forecasting ecological regression constituency clustering