Package | Description |
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moa.cluster | |
moa.evaluation | |
moa.gui.visualization |
Constructor and Description |
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Clustering(ArrayList<DataPoint> points,
double overlapThreshold,
int initMinPoints) |
Modifier and Type | Class and Description |
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protected class |
CMM_GTAnalysis.CMMPoint
Wrapper class for data points to store CMM relevant attributes
|
Modifier and Type | Field and Description |
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protected DataPoint |
CMM_GTAnalysis.CMMPoint.p
Reference to original point
|
Modifier and Type | Method and Description |
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double |
StatisticalCollection.cindex(Clustering clustering,
ArrayList<DataPoint> points) |
void |
F1.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
EntropyCollection.evaluateClustering(Clustering fclustering,
Clustering hClustering,
ArrayList<DataPoint> points) |
protected abstract void |
MeasureCollection.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
CMM.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
Accuracy.evaluateClustering(Clustering clustering,
Clustering trueClsutering,
ArrayList<DataPoint> points) |
void |
SilhouetteCoefficient.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
General.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
ChangeDetectionMeasures.evaluateClustering(Clustering clustering,
Clustering trueClsutering,
ArrayList<DataPoint> points) |
void |
StatisticalCollection.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
OutlierPerformance.evaluateClustering(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
void |
SSQ.evaluateClustering(Clustering clustering,
Clustering trueClsutering,
ArrayList<DataPoint> points) |
double |
MeasureCollection.evaluateClusteringPerformance(Clustering clustering,
Clustering trueClustering,
ArrayList<DataPoint> points) |
Constructor and Description |
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CMM_GTAnalysis.CMMPoint(DataPoint point,
int id) |
Constructor and Description |
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CMM_GTAnalysis(Clustering trueClustering,
ArrayList<DataPoint> points,
boolean enableClassMerge) |
MembershipMatrix(Clustering foundClustering,
ArrayList<DataPoint> points) |
Modifier and Type | Method and Description |
---|---|
void |
StreamPanel.drawPoint(DataPoint point) |
void |
StreamOutlierPanel.drawPoint(DataPoint point,
boolean bShowDecay,
boolean bRedrawPointImg) |
double |
DataPoint.getDistance(DataPoint other) |
static Color |
PointPanel.getPointColorbyClass(DataPoint point,
float numClasses) |
Modifier and Type | Method and Description |
---|---|
void |
RunVisualizer.drawClusterings(List<DataPoint> points0,
List<DataPoint> points1) |
void |
RunVisualizer.drawClusterings(List<DataPoint> points0,
List<DataPoint> points1) |
void |
StreamPanel.drawGTClustering(Clustering clustering,
List<DataPoint> points,
Color color) |
void |
StreamPanel.drawMacroClustering(Clustering clustering,
List<DataPoint> points,
Color color) |
void |
StreamPanel.drawMicroClustering(Clustering clustering,
List<DataPoint> points,
Color color) |
Constructor and Description |
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PointPanel(DataPoint point,
StreamPanel streamPanel,
Color color)
Type 2: Never be decayed, single color.
|
PointPanel(DataPoint point,
StreamPanel streamPanel,
double decayRate,
double decayThreshold)
Type 1: Possibly be decayed, colored by class label.
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Copyright © 2014 University of Waikato, Hamilton, NZ. All Rights Reserved.