Jump Like A Squirrel: Optimized Execution Step Order for Anytime Random Forest Inference

TL;DR

This paper introduces an optimized step order for anytime inference in random forests, improving prediction accuracy in resource-limited scenarios by executing decision trees at the step level.

Contribution

It presents a novel approach to order decision tree steps in random forests for anytime inference, including optimal and heuristic algorithms to maximize accuracy.

Findings

Backward Squirrel Order achieves 94% of the optimal accuracy.

Step-level execution enhances anytime inference in resource-constrained systems.

Heuristic methods perform close to the optimal solution.

Abstract

Due to their efficiency and small size, decision trees and random forests are popular machine learning models used for classification on resource-constrained systems. In such systems, the available execution time for inference in a random forest might not be sufficient for a complete model execution. Ideally, the already gained prediction confidence should be retained. An anytime algorithm is designed to be able to be aborted anytime, while giving a result with an increasing quality over time. Previous approaches have realized random forests as anytime algorithms on the granularity of trees, stopping after some but not all trees of a forest have been executed. However, due to the way decision trees subdivide the sample space in every step, an increase in prediction quality is achieved with every additional step in one tree. In this paper, we realize decision trees and random forest as anytime algorithms on the granularity of single steps in trees. This approach opens a design space to define the step order in a forest, which has the potential to optimize the mean accuracy. We propose the Optimal Order, which finds a step order with a maximal mean accuracy in exponential runtime and the polynomial runtime heuristics Forward Squirrel Order and Backward Squirrel Order, which greedily maximize the accuracy for each additional step taken down and up the trees, respectively. Our evaluation shows, that the Backward Squirrel Order performs $\sim94\%$ as well as the Optimal Order and $\sim99\%$ as well as all other step orders.