# Interfering Paths in Decision Trees: A Note on Deodata Predictors

arXiv: https://arxiv.org/abs/2202.12064 · HTML: https://mlsanity.com/paper/2202.12064/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 3 references that are in the map.
- First posted on arXiv 24 Feb 2022.

## Builds on (most cited first, 1 of 1)

- [Collapsing the Decision Tree: the Concurrent Data Predictor](https://mlsanity.com/paper/2108.03887/) (2021)

## Built on by (most cited first, 1 of 1)

- [Accuracy Convergent Field Predictors](https://mlsanity.com/paper/2205.03712/) (2022)

## Abstract (arXiv)

A technique for improving the prediction accuracy of decision trees is proposed. It consists in evaluating the tree's branches in parallel over multiple paths. The technique enables predictions that are more aligned with the ones generated by the nearest neighborhood variant of the deodata algorithms. The technique also enables the hybridization of the decision tree algorithm with the nearest neighborhood variant.