CostCurve

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## weka.classifiers.evaluation
Class CostCurve

    java.lang.Object
      weka.classifiers.evaluation.CostCurve

All Implemented Interfaces:
  RevisionHandler

    public class CostCurve

extends java.lang.Object
implements RevisionHandler

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".

Version:
  $Revision: 1.9 $
Author:
  Mark Hall (mhall@cs.waikato.ac.nz)

Field Summary
`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
`CostCurve()`

Method Summary
`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.
`java.lang.String` | `getRevision()` Returns the revision string.
`static void` | `main(java.lang.String[] args)` Tests the CostCurve generation from the command line.

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### RELATION_NAME

    public static final java.lang.String RELATION_NAME

  The name of the relation used in cost curve datasets

  See Also:
    Constant Field Values

### PROB_COST_FUNC_NAME

    public static final java.lang.String PROB_COST_FUNC_NAME

  attribute name: Probability Cost Function

  See Also:
    Constant Field Values

### NORM_EXPECTED_COST_NAME

    public static final java.lang.String NORM_EXPECTED_COST_NAME

  attribute name: Normalized Expected Cost

  See Also:
    Constant Field Values

### THRESHOLD_NAME

    public static final java.lang.String THRESHOLD_NAME

  attribute name: Threshold

  See Also:
    Constant Field Values

Constructor Detail

### CostCurve

    public CostCurve()

Method Detail

### getCurve

    public Instances getCurve(FastVector predictions)

  Calculates the performance stats for the default class and return results as a set of Instances. The structure of these Instances is as follows:

  - Probability Cost Function
  - Normalized Expected Cost
  - Threshold contains the probability threshold that gives rise to the previous performance values.

  Parameters:
    `predictions` - the predictions to base the curve on
  Returns:
    datapoints as a set of instances, null if no predictions have been made.
  See Also:
    `TwoClassStats`

### getCurve

    public Instances getCurve(FastVector predictions,
                              int classIndex)

  Calculates the performance stats for the desired class and return results as a set of Instances.

  Parameters:
    `predictions` - the predictions to base the curve on
    `classIndex` - index of the class of interest.
  Returns:
    datapoints as a set of instances.

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Returns:
    the revision

### main

    public static void main(java.lang.String[] args)

  Tests the CostCurve generation from the command line. The classifier is currently hardcoded. Pipe in an arff file.

  Parameters:
    `args` - currently ignored

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