论文标题
射击回归;基于随机梯度的合奏
The Shooting Regressor; Randomized Gradient-Based Ensembles
论文作者
论文摘要
引入了一种合奏方法，该方法利用随机和损耗函数梯度来计算预测。多个弱相关的估计值在误差表面上随机采样点上的梯度近似于梯度，并将其汇总为最终溶液。描述了一个缩放参数，该参数控制了整体相关性和精度之间的权衡。描述了用于估计参数最佳值的数值方法。经验结果是通过流行的数据集计算的。这些结果的推论统计数据表明，该方法能够以提高准确性优于现有技术。
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.
