# Accuracy Convergent Field Predictors

arXiv: https://arxiv.org/abs/2205.03712 · HTML: https://mlsanity.com/paper/2205.03712/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 7 references that are in the map.
- First posted on arXiv 7 May 2022.

## Builds on (most cited first, 4 of 4)

- [Collapsing the Decision Tree: the Concurrent Data Predictor](https://mlsanity.com/paper/2108.03887/) (2021)
- [Probabilistic Alternatives to the Gower Distance: A Note on Deodata Predictors](https://mlsanity.com/paper/2201.06355/) (2022)
- [Backtrack Tie-Breaking for Decision Trees: A Note on Deodata Predictors](https://mlsanity.com/paper/2202.03865/) (2022)
- [Interfering Paths in Decision Trees: A Note on Deodata Predictors](https://mlsanity.com/paper/2202.12064/) (2022)

## Abstract (arXiv)

Several predictive algorithms are described. Highlighted are variants that make predictions by superposing fields associated to the training data instances. They operate seamlessly with categorical, continuous, and mixed data. Predictive accuracy convergence is also discussed as a criteria for evaluating predictive algorithms. Methods are described on how to adapt algorithms in order to make them achieve predictive accuracy convergence.