Disease Classification Model Based on Qubit Neural Tree Networks

This paper introduces a quantum-inspired Qubit neural tree networks with improved Qubit neuron, overlayer connections and different phase operation functions for different neurons to construct disease classification model. A hybrid evolutionary algorithm that combines the modified PIPE algorithm with beetle antennae search is also proposed to optimize the structure and parameters of the Qubit neural tree network. Simulation results on two disease classification problems show that this model has more advantages in classification precision, feature selection and structure simplification, especially for classification with multi-class attributes.

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