Shooting Regressor; Randomized Concentrated Based Ensembles（英语：Randomized Concentrated Concentrated）
The Shooting Regressor; Randomized Gradient-Based Ensembles
摘要：
介绍了一种集成方法，该方法利用随机化和损失函数梯度来计算预测。多个弱相关估计近似误差表面上随机采样点处的梯度，并聚集成最终解。描述了控制系综相关性和精度之间的权衡的缩放参数。数值方法估计的参数的最佳值进行说明。经验结果是在一个流行的数据集上计算的。对这些结果的推断统计表明，该方法能够在提高准确性方面优于现有技术。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
