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