InputMappedClassifier

Package

weka.classifiers.misc

Synopsis

Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure. Model attributes that are not found in the incoming instances receive missing values, so do incoming nominal attribute values that the classifier has not seen before. A new classifier can be trained or an existing one loaded from a file.

Options

The table below describes the options available for InputMappedClassifier.

Option	Description
classifier	The base classifier to be used.
ignoreCaseForNames	Ignore case when matching attribute names and nomina values.
modelPath	Set the path from which to load a model. Loading occurs when the first test instance is received. Environment variables can be used in the supplied path.
suppressMappingReport	Don't output a report of model-to-input mappings.
trim	Trim white space from each end of attribute names and nominal values before matching.

Capabilities

The table below describes the capabilities of InputMappedClassifier.

Capability	Supported
Class	Numeric class, Nominal class, Missing class values, Date class, Binary class
Attributes	Date attributes, Binary attributes, String attributes, Nominal attributes, Empty nominal attributes, Unary attributes, Numeric attributes, Missing values
Min # of instances	0