The Preliminary Attribute Check tests the underlying classifier against the DataTable specification at the inport of the node. Columns that are compatible with the classifier are marked with a green 'ok'. Columns which are potentially not compatible are assigned a red error message.
Important: If a column is marked as 'incompatible', it does not necessarily mean that the classifier cannot be executed! Sometimes, the error message 'Cannot handle String class' simply means that no nominal values are available (yet). This may change during execution of the predecessor nodes.
Capabilities: [Nominal attributes, Binary attributes, Unary attributes, Empty nominal attributes, Numeric attributes, Date attributes, Missing values, Nominal class, Binary class, Missing class values]
Dependencies: [Nominal attributes, Binary attributes, Unary attributes, Empty nominal attributes, Numeric attributes, Date attributes, String attributes, Relational attributes, Missing values, No class, Nominal class, Binary class, Unary class, Empty nominal class, Numeric class, Date class, String class, Relational class, Missing class values, Only multi-Instance data]
min # Instance: 1
S: Random number seed.
(default 1)
I: Number of iterations.
(default 10)
D: If set, classifier is run in debug mode and
may output additional info to the console
W: Full name of base classifier.
(default: weka.classifiers.trees.RandomTree)
:
K: Number of attributes to randomly investigate
(<0 = int(log_2(#attributes)+1)).
M: Set minimum number of instances per leaf.
S: Seed for random number generator.
(default 1)
depth: The maximum depth of the tree, 0 for unlimited.
(default 0)
N: Number of folds for backfitting (default 0, no backfitting).
U: Allow unclassified instances.
D: If set, classifier is run in debug mode and
may output additional info to the console
