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java.lang.Objectweka.classifiers.evaluation.CostCurve
public class CostCurve
Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes. For example, the typical threshold value of 0.5 means the predicted probability of "positive" must be higher than 0.5 for the instance to be predicted as "positive".
Field Summary | |
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static java.lang.String |
NORM_EXPECTED_COST_NAME
attribute name: Normalized Expected Cost |
static java.lang.String |
PROB_COST_FUNC_NAME
attribute name: Probability Cost Function |
static java.lang.String |
RELATION_NAME
The name of the relation used in cost curve datasets |
static java.lang.String |
THRESHOLD_NAME
attribute name: Threshold |
Constructor Summary | |
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CostCurve()
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Method Summary | |
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Instances |
getCurve(FastVector predictions)
Calculates the performance stats for the default class and return results as a set of Instances. |
Instances |
getCurve(FastVector predictions,
int classIndex)
Calculates the performance stats for the desired class and return results as a set of Instances. |
static void |
main(java.lang.String[] args)
Tests the CostCurve generation from the command line. |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final java.lang.String RELATION_NAME
public static final java.lang.String PROB_COST_FUNC_NAME
public static final java.lang.String NORM_EXPECTED_COST_NAME
public static final java.lang.String THRESHOLD_NAME
Constructor Detail |
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public CostCurve()
Method Detail |
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public Instances getCurve(FastVector predictions)
predictions
- the predictions to base the curve on
TwoClassStats
public Instances getCurve(FastVector predictions, int classIndex)
predictions
- the predictions to base the curve onclassIndex
- index of the class of interest.
public static void main(java.lang.String[] args)
args
- currently ignored
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