论文标题
通过有效的变量选择，改善$ k $最近的邻居学习的预测性能
Improving the Predictive Performances of $k$ Nearest Neighbors Learning by Efficient Variable Selection
论文作者
论文摘要
本文在计算上表明，由于预测变量有效地选择了$ K $最近的邻居的预测性能的急剧提高。我们显示了模拟和现实世界的数据，这本小说反复接近逐步选择下的表现回归模型
This paper computationally demonstrates a sharp improvement in predictive performance for $k$ nearest neighbors thanks to an efficient forward selection of the predictor variables. We show both simulated and real-world data that this novel repeatedly approaches outperformance regression models under stepwise selection
