Package

weka.classifiers.functions

Synopsis

Builds Fisher's Linear Discriminant function. The threshold is selected so that the separator is half-way between centroids. The class must be binary and all other attributes must be numeric. Missing values are not permitted. Constant attributes are removed using RemoveUseless. No standardization or normalization of attributes is performed.

This classifier can be found in the discriminantAnalysis package.

Options

The table below describes the options available for FLDA.

Option	Description
batchSize	The preferred number of instances to process if batch prediction is being performed. More or fewer instances may be provided, but this gives implementations a chance to specify a preferred batch size.
debug	If set to true, classifier may output additional info to the console.
doNotCheckCapabilities	If set, classifier capabilities are not checked before classifier is built (Use with caution to reduce runtime).
numDecimalPlaces	The number of decimal places to be used for the output of numbers in the model.
ridge	The value of the ridge parameter.

Capabilities

The table below describes the capabilities of FLDA.

Capability	Supported
Class	Binary class, Missing class values
Attributes	Numeric attributes
Min # of instances	0