원문정보
초록
영어
This paper has been explored information data prediction implementation access based on data mining combination model. With data mining technology as the entry point and in combination with the analysis on information data prediction characteristics. Research on variable substitution to non-linear regression forecast model precision's influence, and seek the modeling method that can improve the forecast precision. Based on the Data mining, the transform in space and the weighted processing combined method, make full use of information that the primary data provide. Given modeling method of combination forecast model based on the Data mining. Based on Data mining’s combination forecast model’s modeling method can reduce the serious influence that the variable substitution brings and has fully used useful information in the primary data. It obviously improved the accuracy of the prediction model.
목차
1. Introduction
2. Data Clustering, Classification and Feature Selection Algorithm
Efficient Rather than Accurate
Relevancy Rather than Causality
Information Data Prediction Access Based on Data Mining Combination Model
Form of the Nonlinear Mathematical Model
Method to Approximate Common Nonlinear Mathematical Models to Regression Model Parameters
Improvement of Approximating Common Nonlinear Mathematical Models to Regression Model Parameters
Method of the Combination Information Forecasting Model Based on Data Mining
In Empirical Analysis
Conclusion
References