netkit.classifiers.active
Class ComparatorLabeler
java.lang.Object
netkit.classifiers.active.PickLabelStrategyImp
netkit.classifiers.active.ComparatorLabeler
- All Implemented Interfaces:
- PickLabelStrategy, Configurable
public class ComparatorLabeler
- extends PickLabelStrategyImp
This class does a comparison between multiple active learning strategies. Currently,
the comparisons are hard-coded to compare against greedy truth. It then compares against:
- ERM
- uncertainty
- graphcentrality using weighted closeness (global)
- graphcentrality using closeness (global)
- graphcentrality using weighted betweenness (global)
- graphcentrality using betweenness (global)
- graphcentrality using clustering + closeness
- graphcentrality using clustering + closeness [size rank]
- graphcentrality using clustering + closeness [labeldist rank]
- graphcentrality using clustering + closeness [erm rank]
- graphcentrality using clustering + weighted closeness
- graphcentrality using clustering + weighted closeness [size rank]
- graphcentrality using clustering + weighted closeness [labeldist rank]
- graphcentrality using clustering + weighted closeness [erm rank]
Comparison shows:
- The rank of the greedy truth node in each of the other strategies (when applicable)
- The rank of the ERM top node in each of the other strategies (when applicable)
- The greedy truth rank for the top node in each of the other strategies
- The ERM rank for the top node in each of the other strategies
- Author:
- sofmac
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
ComparatorLabeler
public ComparatorLabeler()
configure
public void configure(Configuration config)
- Specified by:
configure
in interface Configurable
- Overrides:
configure
in class PickLabelStrategyImp
initialize
public void initialize(NetworkLearner nl,
DataSplit split)
- Description copied from interface:
PickLabelStrategy
- Initialize the label strategy by providing a reference to the NetworkLeaner
object that calls the strategy, thereby giving it access to all information
it is likely to need. This should re-initialize the strategy if
it has any cached values from prior calls.
- Specified by:
initialize
in interface PickLabelStrategy
- Overrides:
initialize
in class PickLabelStrategyImp
- Parameters:
nl
- The NetworkLearner object that will be calling this strategy.split
- The initial train/test split that this will be used on
pickNodes
protected PickLabelStrategy.LabelNode[] pickNodes(Estimate predictions,
int maxPicks)
- Maxpicks are ignored. We ever only look at the top-1 pick from all strategies and only
follow the top pick from the
- Specified by:
pickNodes
in class PickLabelStrategyImp
maxPicks
- how many nodes should it pick at maximum (this iteration)
- Returns:
- An array of Node objects that should receive labels.
null
is returned if done.
getDescription
public java.lang.String getDescription()
getName
public java.lang.String getName()
getShortName
public java.lang.String getShortName()