The Shooting Regressor; Randomized Gradient-Based Ensembles

• URL: http://arxiv.org/abs/2009.06172v1
• Date: Mon, 14 Sep 2020 03:20:59 GMT
• Title: The Shooting Regressor; Randomized Gradient-Based Ensembles
• Authors: Nicholas Smith
• Abstract summary: An ensemble method is introduced that utilizes randomization and loss function gradients to compute a prediction. Multiple weakly-correlated estimators approximate the gradient at randomly sampled points on the error surface and are aggregated into a final solution.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: An ensemble method is introduced that utilizes randomization and loss function gradients to compute a prediction. Multiple weakly-correlated estimators approximate the gradient at randomly sampled points on the error surface and are aggregated into a final solution. A scaling parameter is described that controls a trade-off between ensemble correlation and precision. Numerical methods for estimating optimal values of the parameter are described. Empirical results are computed over a popular dataset. Inferential statistics on these results show that the method is capable of outperforming existing techniques in terms of increased accuracy.

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