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- W1987291222 abstract "In traditional Bayesian classification data mining methods, there may be defects such as predictions unreliable because the selected predictors are little or not related with the target factor. this paper analyzes the correlation between predictors and the target factor using correlation coefficient based on Bayesian classification model and combines with Hadoop distributed file system and parallel programming models to explore an improved algorithm. The experiments show that this method not only makes the prediction more reliable but also saves resources and improves the efficiency of the algorithm greatly. In addition, it is suitable for massive data processing." @default.
- W1987291222 created "2016-06-24" @default.
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- W1987291222 creator A5030823415 @default.
- W1987291222 date "2014-09-01" @default.
- W1987291222 modified "2023-09-25" @default.
- W1987291222 title "A Research Using Correlation Coefficient to Make Bayesian Classification Data Mining" @default.
- W1987291222 cites W2140785063 @default.
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- W1987291222 doi "https://doi.org/10.4028/www.scientific.net/amm.631-632.18" @default.
- W1987291222 hasPublicationYear "2014" @default.
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