• Corpus ID: 245537480

Improving Nonparametric Classification via Local Radial Regression with an Application to Stock Prediction

@article{Cao2021ImprovingNC,
  title={Improving Nonparametric Classification via Local Radial Regression with an Application to Stock Prediction},
  author={Ruixing Cao and Akifumi Okuno and Kei Nakagawa and Hidetoshi Shimodaira},
  journal={ArXiv},
  year={2021},
  volume={abs/2112.13951}
}
For supervised classification problems, this paper considers estimating the query’s label probability through local regression using observed covariates. Well-known nonparametric kernel smoother and knearest neighbor (k-NN) estimator, which take label average over a ball around the query, are consistent but asymptotically biased particularly for a large radius of the ball. To eradicate such bias, local polynomial regression (LPoR) and multiscale k-NN (MS-k-NN) learn the bias term by local… 

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