Research Article
Mining Outlier Data in Mobile Internet-Based Large Real-Time Databases
Table 1
Parameters used to classify outlier data with the decision-tree in large real-time databases.
| Title | Explanation | Default |
| Binary splits | The binary tree method is used to divide noun attributes. | False | Confidence factor | Prune confidence factors (factors smaller than the given value are pruned from the subtree). | 0.25 | MinNumObj | The number of instantiation that will be pruned from leaf nodes. | 2 | NumFolds | This value is used to reduce the error-pruning data flow; the remaining data are used to construct the tree. | 3 | ReducedErrorPruning | Prune with the error-reduction method. | False | Seed | Prune with error-reduction method and transplant subtree seeds of random data. | 1 | Unpruned | Determines whether result tree has been pruned. | False |
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