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Guo and Milanović presented a probabilistic framework to evaluate the accuracy of data mining tools applied for online prediction of transient stability [14], enabling the comprehensive analysis of performance of different implementations.
Moreover, we also noticed that, compared with the 96% overall accuracy of data mining method in prediction of NSCLC prognosis and the 88.4% accuracy of gene profiling in predicting RLNM in colorectal cancer (Takahashi et al, 2007; Watanabe et al, 2009), our SVM model reached a lower (72.3%) predictive accuracy in refining RLNM status for RC patients.
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Some scholars have applied artificial intelligence technology in heterogeneous networks and improved the accuracy and efficiency of data mining.
The high degree of accuracy of developed models is a good example of data mining's contribution to medicine [ 21].
Investigating the impacts of data mining techniques in increasing forecasting accuracy is another objective of this research, where four sets of data are examined using each technique.
Resuming, preserving the differences, the application of data mining techniques allowed building high accuracy models, with results not lower than the traditional methods found in the literature.
A micro-economic view of data mining.
The social impacts of data mining are discussed, including ubiquitous and invisible data mining, and privacy-preserving data mining.
Additionally, task-driven data mining concepts and principles are elaborated with the help of data mining concepts and techniques.
The mining of frequent itemsets is a fundamental and important task of data mining.
Temporal data mining is the application of data mining techniques to data that takes the time dimension into account.
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