Package

weka.classifiers.mi

Synopsis

This classifier tries to find a suitable ball in the multiple-instance space, with a certain data point in the instance space as a ball center. The possible ball center is a certain instance in a positive bag. The possible radiuses are those which can achieve the highest classification accuracy. The model selects the maximum radius as the radius of the optimal ball.

For more information about this algorithm, see:

Peter Auer, Ronald Ortner: A Boosting Approach to Multiple Instance Learning. In: 15th European Conference on Machine Learning, 63-74, 2004.

Options

The table below describes the options available for MIOptimalBall.

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

Capabilities

The table below describes the capabilites of MIOptimalBall.

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