Decision tree model

About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.

Decision tree model for early diagnosis of lung cancer

Abstract: The invention relates to the technical field of medical diagnostic, and discloses a decision tree model for early diagnosis of lung cancer, which is characterized in that: a protein chip and time-of-flight mass spectrometry system is used to detect the peripheral serum samples of early lung cancer patients so as to find a specific protein peak obviously different from that of lung cancer patients, and a decision tress model is obtained by a decision tree algorithm according to the mass to charge ratio (m / z) of each protein peak. The decision tree model can be preliminarily used for diagnosis of the lung cancer only by analyzing the m / z of corresponding protein in serum of the detected person and the model provided by the invention. The prediction accuracy rate is 79%.

A Hybrid Optimization Method for Neural Tree Network Model

Abstract: Neural tree network model has been successfully applied to solving large numbers of complex nonlinear problems in control area. The optimization of neural tree model contains: structure and parameter, the major problem in evolving structure without parameter information was noisy fitness evaluation problem, so an improved genetic programming algorithm is proposed to synthesize the optimization process. Simulation results on two time series prediction problems show that the proposed strategy is a potential method with better performance and effectiveness.

The complexity of classical and quantum branching programs: a communication complexity approach

Abstract: We present a survey of the communication point of view for a complexity lower bounds proof technique for classical (deterministic, nondeterministic and randomized) and quantum models of branching programs.