MIOptimalBall
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 |