Detail of computed results reported
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Specifies the detail of computed results reported. If Minimal results is requested, only the final tree will be displayed; if Comprehensive detail is requested, various other statistical summaries are reported as well; if All results is requested, various node statistics and graphs are reported as well. Note that observational statistics (predicted values) are available as an option.
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Stopping option for pruning
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One of the ways by which the size of the tree can be checked, is by pruning the tree, i.e., by removing parts of trees with the aim of computing the right-sized tree. If the dependent variable is continuous (regression), then the measure used is the variance of cases in a node. Select the Prune on variance option button to prune on the basis of variance. Another way to prune in the case of a categorical variable (classification) is on the basis of fraction of objects of one or more classes in the node. In the GC&RT module, this is done by the FACT-style direct stopping; splitting on the predictor variables continues until all the terminal nodes in the classification tree are pure. If FACT-style direct stopping is selected as the stopping rule, then the value in the Fraction of objects box is used to control the classification tree selected as the right-sized tree.
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Minimum n per node
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If a pruning method is selected in the Stopping rule group box, i.e., Prune on misclassification error or Prune on deviance, enter a value in the Minimum n box to control when split selection stops and pruning begins. Unless splitting is terminated by one of the other criteria specified on this tab, the tree-building process will continue until no more splits can be applied without creating nodes with fewer cases than specified in this edit field.
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Minimum child node size to stop
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Use this option to control the smallest permissible number in a child node, for a split to be applied. While the Minimum n of cases parameter determines whether an additional split is considered at any particular node, the Minimum n in child node parameter determines whether a split will be applied, depending on whether any of the two resultant child nodes will be smaller (have fewer cases) than n as specified via this option.
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Fraction of objects
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If FACT-style direct stopping is selected as the Stopping rule (see above), the value in the Fraction of objects box is used to control the classification tree selected as the right-sized tree.
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Maximum number of nodes
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The value supplied in the Maximum n nodes box will be used for stopping on the basis of the number of nodes in the classification tree. Each time a parent node is split, the total number of nodes in the tree is examined, and the splitting is stopped if this number exceeds the number specified in Maximum n nodes box.
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Maximum number of levels in tree
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Maximum number of levels in tree.
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Number of surrogates
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Specifies the number of surrogates for surrogate splits.
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Creates predicted classes
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Creates observational statistics (predicted values).
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Generates data source, if N for input less than
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Generates a data source for further analyses with other Data Miner nodes if the input data source has fewer than k observations, as specified in this edit field; note that parameter k (number of observations) will be evaluated against the number of observations in the input data source, not the number of valid or selected observations.
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