Author: scooter
Date: 2011-08-19 17:23:14 -0700 (Fri, 19 Aug 2011)
New Revision: 26611
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
Log:
kmedoid clean-up. Also force "ignoreMissing" for kmedoid and kmeans.
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
2011-08-20 00:23:14 UTC (rev 26611)
@@ -145,10 +145,12 @@
"Cluster attributes as well
as nodes",
Tunable.BOOLEAN, new
Boolean(false)));
+/*
// For expression data, we might want to exclude missing data
clusterProperties.add(new Tunable("ignoreMissing",
"Ignore nodes with no data",
- Tunable.BOOLEAN, new
Boolean(false)));
+ Tunable.BOOLEAN, new
Boolean(true)));
+*/
// Whether or not to create groups
clusterProperties.add(new Tunable("createGroups",
@@ -187,9 +189,11 @@
if ((t != null) && (t.valueChanged() || force))
selectedOnly = ((Boolean) t.getValue()).booleanValue();
+/*
t = clusterProperties.get("ignoreMissing");
if ((t != null) && (t.valueChanged() || force))
ignoreMissing = ((Boolean) t.getValue()).booleanValue();
+*/
t = clusterProperties.get("createGroups");
if ((t != null) && (t.valueChanged() || force))
@@ -223,7 +227,7 @@
KCluster algorithm = new KCluster(attributeArray,
distanceMetric, logger, monitor);
algorithm.setCreateGroups(createGroups);
- algorithm.setIgnoreMissing(ignoreMissing);
+ algorithm.setIgnoreMissing(true);
algorithm.setSelectedOnly(selectedOnly);
algorithm.setDebug(debug);
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
2011-08-20 00:23:14 UTC (rev 26611)
@@ -117,7 +117,7 @@
// Start by calculating the pairwise distances
double[][] distances = new
double[matrix.nRows()][matrix.nRows()];
for (int i = 0; i < matrix.nRows(); i++) {
- for (int j = i; j < matrix.nRows(); j++) {
+ for (int j = 0; j < matrix.nRows(); j++) {
distances[i][j] = metric.getMetric(matrix,
matrix, matrix.getWeights(), i, j);
}
}
@@ -182,8 +182,10 @@
for (int row = 0; row < matrix.nRows(); row++) {
if (clusterid[row] == cluster) {
double distance = metric.getMetric(matrix,
cdata, matrix.getWeights(), row, cluster);
- if (distance < minDistance)
+ if (distance < minDistance) {
medoid = row;
+ minDistance = distance;
+ }
}
}
return medoid;
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
2011-08-20 00:23:14 UTC (rev 26611)
@@ -146,10 +146,12 @@
"Cluster attributes as well
as nodes",
Tunable.BOOLEAN, new
Boolean(false)));
+/*
// For expression data, we might want to exclude missing data
clusterProperties.add(new Tunable("ignoreMissing",
"Ignore nodes with no data",
Tunable.BOOLEAN, new
Boolean(false)));
+*/
// Whether or not to create groups
clusterProperties.add(new Tunable("createGroups",
@@ -188,9 +190,11 @@
if ((t != null) && (t.valueChanged() || force))
selectedOnly = ((Boolean) t.getValue()).booleanValue();
+/*
t = clusterProperties.get("ignoreMissing");
if ((t != null) && (t.valueChanged() || force))
ignoreMissing = ((Boolean) t.getValue()).booleanValue();
+*/
t = clusterProperties.get("createGroups");
if ((t != null) && (t.valueChanged() || force))
@@ -224,7 +228,7 @@
KMCluster algorithm = new KMCluster(attributeArray,
distanceMetric, logger, monitor);
algorithm.setCreateGroups(createGroups);
- algorithm.setIgnoreMissing(ignoreMissing);
+ algorithm.setIgnoreMissing(true); // KMedoid doesn't
handle missing data well
algorithm.setSelectedOnly(selectedOnly);
algorithm.setDebug(debug);
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