Package

weka.classifiers.mi

Synopsis

Re-implement the Diverse Density algorithm, changes the testing procedure.

Oded Maron (1998). Learning from ambiguity.

O. Maron, T. Lozano-Perez (1998). A Framework for Multiple Instance Learning. Neural Information Processing Systems. 10.

The table below describes the options available for MIDD.

Option	Description
debug	If set to true, classifier may output additional info to the console.
filterType	The filter type for transforming the training data.

The table below describes the capabilites of MIDD.

Capability	Supported
Class	Missing class values, Binary class
Attributes	Unary attributes, Relational attributes, Empty nominal attributes, Nominal attributes, Binary attributes, Missing values
Other	Only multi-Instance data
Min # of instances	1