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