Taraba Peter
Independent Researcher, Fort Lauderdale, FL, United States.
Front Artif Intell. 2023 Feb 24;6:1144886. doi: 10.3389/frai.2023.1144886. eCollection 2023.
We derive blending coefficients for the optimal blend of multiple independent prediction models with normal (Gaussian) distribution as well as the variance of the final blend. We also provide lower and upper bound estimation for the final variance and we compare these results with machine learning with counts, where only binary information (feature says yes or no only) is used for every feature and the majority of features agreeing together make the decision.
我们推导了具有正态（高斯）分布的多个独立预测模型的最优混合的混合系数以及最终混合的方差。我们还提供了最终方差的上下界估计，并将这些结果与基于计数的机器学习进行比较，在基于计数的机器学习中，每个特征仅使用二元信息（特征仅表示是或否），并且大多数特征一致时做出决策。
