Specifies the minimum dependency probability between input and output attributes. This value is used to limit the size of the content generated by the algorithm. This property can be set from 0 to 1. Increasing this value reduces the number of attributes in the model.
Specifies the metadata cached for the linking object, as well as the behavior upon any changes to the underlying linked object. ...
Specifies the method used to calculate the split score. The available methods are: Entropy (1), Bayesian with K2 Prior (3), ...
Specifies the method used to discretize (group) the members of the attribute. The number of buckets created by discretizing ...
Specifies the method used to fill the gaps in historical data. By default, irregular gaps or ragged edges in data are not ...
Specifies the minimum dependency probability between input and output attributes. This value is used to limit the size of ...
Specifies the minimum number of cases that a leaf node must contain. Setting this value to less than 1 specifies the minimum ...
Specifies the minimum number of cases that must contain the itemset before generating a rule. Setting this value to less ...
Specifies the minimum probability that a rule is true. For example, setting this value to 0.5 specifies that no rule with ...
Specifies the number of buckets in which to discretize (group) members of the attribute. The method used to discretize the ...