A nonparametric ensemble binary classifier and its statistical properties

Tanujit Chakraborty, Ashis Kumar Chakraborty and C.A. Murthy

Statistics & Probability Letters, 2019, vol. 149, issue C, 16-23

Abstract: In this work, we propose an ensemble of classification trees (CT) and artificial neural networks (ANN). Several statistical properties including universal consistency and upper bound of an important parameter of the proposed classifier are shown. Numerical evidence is also provided using various real-life data sets to assess the performance of the model. Our proposed nonparametric ensemble classifier does not suffer from the “curse of dimensionality” and can be used in a wide variety of feature selection cum classification problems. Performance of the proposed model is quite better when compared to many other state-of-the-art models used for similar situations.

Keywords: Classification trees; Neural networks; Hybrid model; Consistency; Medical data (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.spl.2019.01.021

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