Abstract

This study has been explored food 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 food 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.

Keywords:

Data mining technology, data prediction, non-linear model, space trans-formation,

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Competing interests

The authors have no competing interests.

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