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.

Fast Time-Varying Channel Model Research for Data Processing of Wireless Communication

Abstract: With the complexity and uncertainty of mobile communication network environment, solving the classical mathematical analysis also becomes more complicated. The model tree of basis function method based on Fourier series is proposed in this paper. Model tree method is the improvement of regression tree analysis. Basis function applied here is four-order Fourier series. When the Fourier coefficients are calculated, the Gauss elimination method is implemented for solving equations. The complexity of the algorithm is n3log(n).

Heuristic Mode Research and Application of Decision Tree Algorithm

Abstract: Decision tree, as an important classification algorithm in data mining, has been successfully applied in many fields. In this paper, based on the analysis of the essential characteristics of decision tree algorithm, we give a leaf criterion for multi-decision values of decision attribute, and establish a mathematical model for the selection for expanded attributes; also we give a concrete model based on quasi-linear function (denoted by QASM). Finally, we compare and analyze the performance of QASM combining with ID3 algorithm through an example. The results show that QASM can not only effectively merge the decision consciousness into decision-making process in a quantitative way, but also the computational complexity is lower than that of ID3 algorithm.

Research and Application of Credit Score Based on Decision Tree Model

Abstract: In order to timely and properly analyse the customer credit assessment, and to speed up the decision-making speed, here introduced the application of data mining technology used in the bank on the users” evaluation, and establish a decision tree model of customer credit evaluation which is aimed at improving the credit rating quality . And introduced the basic process of decision tree algorithm. Bank customer’s credit is classified as background. Using the decision tree algorithm C4.5 as the most classic tools, specific studies of business understanding, data understanding, data preparation, modeling, evaluation and implementation of aspects of publishing have been done. Customer credit, using the decision tree classification algorithm, obtained a series of decision rules with which a bank to make the right decisions.

A Survey on Latent Tree Models and Applications

Abstract: In data analysis, latent variables play a central role because they help provide powerful insights into a wide variety of phenomena, ranging from biological to human sciences. The latent tree model, a particular type of probabilistic graphical models, deserves attention. Its simple structure - a tree - allows simple and efficient inference, while its latent variables capture complex relationships. In the past decade, the latent tree model has been subject to significant theoretical and methodological developments. In this review, we propose a comprehensive study of this model. First we summarize key ideas underlying the model. Second we explain how it can be efficiently learned from data. Third we illustrate its use within three types of applications: latent structure discovery, multidimensional clustering, and probabilistic inference. Finally, we conclude and give promising directions for future researches in this field.

Complex electromechanical system reliability modeling method based on probability behavior tree

Abstract: The invention discloses a complex electromechanical system reliability modeling method based on a probability behavior tree. The method comprises the following steps that: 1) combining the function execution logic of a complex electromechanical system with the hierarchy of an analyzed problem to determine the composition unit and the state transition of the system; 2) for each composition unit ofthe electromechanical system, establishing the sub-behavior tree model of each composition unit; and 3) utilizing a synchronous event expressed by an input/ output node in the behavior tree model to link the sub-behavior tree model of each unit, and forming a complex electromechanical system reliability model based on the probability behavior tree. By use of the method, the state transition in a complex electromechanical system behavior process can be visually and clearly expressed, a modeling process has good hierarchical characteristics and can be easily maintained, and the method is especially suitable for the complex electromechanical system reliability modeling. On the basis of the model, a probability model detection tool can be used for automatically calculating a reliability index,and the efficiency and the accuracy of the complex electromechanical system reliability evaluation can be improved.