本文整理汇总了Java中weka.core.DistanceFunction类的典型用法代码示例。如果您正苦于以下问题：Java DistanceFunction类的具体用法？Java DistanceFunction怎么用？Java DistanceFunction使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
DistanceFunction类属于weka.core包，在下文中一共展示了DistanceFunction类的16个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Java代码示例。
示例1: setOptions
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Parses a given list of options. Valid options are:
*
* <!-- options-start --> <!-- options-end -->
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
@Override
public void setOptions(String[] options) throws Exception {
String nnSearchClass = Utils.getOption('A', options);
if (nnSearchClass.length() != 0) {
String nnSearchClassSpec[] = Utils.splitOptions(nnSearchClass);
if (nnSearchClassSpec.length == 0) {
throw new Exception("Invalid DistanceFunction specification string.");
}
String className = nnSearchClassSpec[0];
nnSearchClassSpec[0] = "";
setDistanceFunction((DistanceFunction) Utils.forName(
DistanceFunction.class, className, nnSearchClassSpec));
} else {
setDistanceFunction(new EuclideanDistance());
}
setMeasurePerformance(Utils.getFlag('P', options));
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:28，代码来源:NearestNeighbourSearch.java
示例2: setOptions
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Parses a given list of options. Valid options are:
*
<!-- options-start -->
<!-- options-end -->
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
public void setOptions(String[] options) throws Exception {
String nnSearchClass = Utils.getOption('A', options);
if(nnSearchClass.length() != 0) {
String nnSearchClassSpec[] = Utils.splitOptions(nnSearchClass);
if(nnSearchClassSpec.length == 0) {
throw new Exception("Invalid DistanceFunction specification string.");
}
String className = nnSearchClassSpec[0];
nnSearchClassSpec[0] = "";
setDistanceFunction( (DistanceFunction)
Utils.forName( DistanceFunction.class,
className, nnSearchClassSpec) );
}
else {
setDistanceFunction(new EuclideanDistance());
}
setMeasurePerformance(Utils.getFlag('P',options));
}
开发者ID:dsibournemouth，项目名称:autoweka，代码行数:30，代码来源:NearestNeighbourSearch.java
示例3: useCosine
import weka.core.DistanceFunction; //导入依赖的package包/类
private IBk useCosine() {
IBk ibk = new IBk();
Instances data = ClassificationModel.getInstance().getInstances();
Normalize normalizer = new Normalize();
try {
normalizer.setInputFormat(data);
// Euclidean Distance working over normalized instances = Cosine Similarity according to Foundations of Statistical Natural Processing Language p.301
// As long as attribute normalization is disabled.
Instances normalizedInstances;
normalizedInstances = Filter.useFilter(data, normalizer);
ClassificationModel.getInstance().setInstances(normalizedInstances);
DistanceFunction df = new EuclideanDistance();
((EuclideanDistance) df).setDontNormalize(true);
ibk.getNearestNeighbourSearchAlgorithm().setDistanceFunction(df);
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
return ibk;
}
开发者ID:a-n-d-r-e-i，项目名称:seagull，代码行数:24，代码来源:Classification.java
示例4: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* sets the distance function to use for instance comparison.
*
* @param df the new distance function to use
* @throws Exception if instances cannot be processed
*/
public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance)
&& !(df instanceof ManhattanDistance)) {
throw new Exception(
"SimpleKMeans currently only supports the Euclidean and Manhattan distances.");
}
m_DistanceFunction = df;
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:15，代码来源:SimpleKMeans.java
示例5: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* sets the distance function to use for instance comparison.
*
* @param df the new distance function to use
* @throws Exception if instances cannot be processed
*/
public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance)
&& !(df instanceof ManhattanDistance)) {
throw new Exception(
"KMeansPlusPlus only supports the Euclidean and Manhattan distances.");
}
m_DistanceFunction = df;
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:15，代码来源:KMeansPlusPlusSC.java
示例6: getDistanceSpec
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Gets the distance specification string, which contains the class name of
* the distance and any options to the distance
*
* @return the distance string.
*/
protected String getDistanceSpec() {
DistanceFunction c = getDistance();
if (c instanceof OptionHandler) {
return c.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)c).getOptions());
}
return c.getClass().getName();
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:16，代码来源:FilteredDistance.java
示例7: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Sets the distance function to use for nearest neighbour search. Currently
* only EuclideanDistance is supported.
*
* @param df the distance function to use
* @throws Exception if not EuclideanDistance
*/
@Override
public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance)) {
throw new Exception("CoverTree currently only works with "
+ "EuclideanDistanceFunction.");
}
m_DistanceFunction = m_EuclideanDistance = (EuclideanDistance) df;
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:16，代码来源:CoverTree.java
示例8: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* sets the distance function to use for nearest neighbour search.
*
* @param df the distance function to use
* @throws Exception if not EuclideanDistance
*/
public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance))
throw new Exception("KDTree currently only works with "
+ "EuclideanDistanceFunction.");
m_DistanceFunction = m_EuclideanDistance = (EuclideanDistance) df;
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:13，代码来源:KDTree.java
示例9: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* sets the distance function to use for instance comparison.
*
* @param df the new distance function to use
* @throws Exception if instances cannot be processed
*/
public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance) &&
!(df instanceof ManhattanDistance)) {
throw new Exception("SimpleKMeans currently only supports the Euclidean and Manhattan distances.");
}
m_DistanceFunction = df;
}
开发者ID:guojiasheng，项目名称:LibD3C-1.1，代码行数:14，代码来源:SimpleKMeans.java
示例10: getDistanceFSpec
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Gets the distance function specification string, which contains the
* class name of the distance function class and any options to it.
*
* @return the distance function specification string
*/
protected String getDistanceFSpec() {
DistanceFunction d = getDistanceF();
if (d instanceof OptionHandler) {
return d.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler) d).getOptions());
}
return d.getClass().getName();
}
开发者ID:williamClanton，项目名称:jbossBA，代码行数:16，代码来源:XMeans.java
示例11: getDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
public DistanceFunction getDistanceFunction() {
return m_DistanceFunction;
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:4，代码来源:HierarchicalClusterer.java
示例12: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
public void setDistanceFunction(DistanceFunction distanceFunction) {
m_DistanceFunction = distanceFunction;
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:4，代码来源:HierarchicalClusterer.java
示例13: setOptions
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Parses a given list of options.
* <p/>
*
* <!-- options-start --> Valid options are:
* <p/>
*
* <!-- options-end -->
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
@Override
public void setOptions(String[] options) throws Exception {
m_bPrintNewick = Utils.getFlag('P', options);
String optionString = Utils.getOption('N', options);
if (optionString.length() != 0) {
Integer temp = new Integer(optionString);
setNumClusters(temp);
} else {
setNumClusters(2);
}
setDistanceIsBranchLength(Utils.getFlag('B', options));
String sLinkType = Utils.getOption('L', options);
if (sLinkType.compareTo("SINGLE") == 0) {
setLinkType(new SelectedTag(SINGLE, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("COMPLETE") == 0) {
setLinkType(new SelectedTag(COMPLETE, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("AVERAGE") == 0) {
setLinkType(new SelectedTag(AVERAGE, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("MEAN") == 0) {
setLinkType(new SelectedTag(MEAN, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("CENTROID") == 0) {
setLinkType(new SelectedTag(CENTROID, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("WARD") == 0) {
setLinkType(new SelectedTag(WARD, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("ADJCOMPLETE") == 0) {
setLinkType(new SelectedTag(ADJCOMPLETE, TAGS_LINK_TYPE));
}
if (sLinkType.compareTo("NEIGHBOR_JOINING") == 0) {
setLinkType(new SelectedTag(NEIGHBOR_JOINING, TAGS_LINK_TYPE));
}
String nnSearchClass = Utils.getOption('A', options);
if (nnSearchClass.length() != 0) {
String nnSearchClassSpec[] = Utils.splitOptions(nnSearchClass);
if (nnSearchClassSpec.length == 0) {
throw new Exception("Invalid DistanceFunction specification string.");
}
String className = nnSearchClassSpec[0];
nnSearchClassSpec[0] = "";
setDistanceFunction((DistanceFunction) Utils.forName(
DistanceFunction.class, className, nnSearchClassSpec));
} else {
setDistanceFunction(new EuclideanDistance());
}
super.setOptions(options);
Utils.checkForRemainingOptions(options);
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:73，代码来源:HierarchicalClusterer.java
示例14: calcRadius
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Calculates the radius of a node.
*
* @param start The start index of the portion in indices array
* that belongs to the node.
* @param end The end index of the portion in indices array
* that belongs to the node.
* @param instList The indices array holding indices of
* instances.
* @param insts The actual instances. instList points to
* instances in this object.
* @param pivot The centre/pivot of the node.
* @param distanceFunction The distance function to use to
* calculate the radius.
* @return The radius of the node.
* @throws Exception If there is some problem calculating the
* radius.
*/
public static double calcRadius(int start, int end, int[] instList,
Instances insts, Instance pivot,
DistanceFunction distanceFunction)
throws Exception {
double radius = Double.NEGATIVE_INFINITY;
for(int i=start; i<=end; i++) {
double dist = distanceFunction.distance(pivot,
insts.instance(instList[i]), Double.POSITIVE_INFINITY);
if(dist>radius)
radius = dist;
}
return Math.sqrt(radius);
}
开发者ID:mydzigear，项目名称:repo.kmeanspp.silhouette_score，代码行数:34，代码来源:BallNode.java
示例15: setOptions
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Parses a given list of options. <p/>
*
<!-- options-start -->
* Valid options are: <p/>
*
<!-- options-end -->
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
public void setOptions(String[] options) throws Exception {
m_bPrintNewick = Utils.getFlag('P', options);
String optionString = Utils.getOption('N', options);
if (optionString.length() != 0) {
Integer temp = new Integer(optionString);
setNumClusters(temp);
}
else {
setNumClusters(2);
}
setDebug(Utils.getFlag('D', options));
setDistanceIsBranchLength(Utils.getFlag('B', options));
String sLinkType = Utils.getOption('L', options);
if (sLinkType.compareTo("SINGLE") == 0) {setLinkType(new SelectedTag(SINGLE, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("COMPLETE") == 0) {setLinkType(new SelectedTag(COMPLETE, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("AVERAGE") == 0) {setLinkType(new SelectedTag(AVERAGE, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("MEAN") == 0) {setLinkType(new SelectedTag(MEAN, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("CENTROID") == 0) {setLinkType(new SelectedTag(CENTROID, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("WARD") == 0) {setLinkType(new SelectedTag(WARD, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("ADJCOMLPETE") == 0) {setLinkType(new SelectedTag(ADJCOMLPETE, TAGS_LINK_TYPE));}
if (sLinkType.compareTo("NEIGHBOR_JOINING") == 0) {setLinkType(new SelectedTag(NEIGHBOR_JOINING, TAGS_LINK_TYPE));}
String nnSearchClass = Utils.getOption('A', options);
if(nnSearchClass.length() != 0) {
String nnSearchClassSpec[] = Utils.splitOptions(nnSearchClass);
if(nnSearchClassSpec.length == 0) {
throw new Exception("Invalid DistanceFunction specification string.");
}
String className = nnSearchClassSpec[0];
nnSearchClassSpec[0] = "";
setDistanceFunction( (DistanceFunction)
Utils.forName( DistanceFunction.class,
className, nnSearchClassSpec) );
}
else {
setDistanceFunction(new EuclideanDistance());
}
Utils.checkForRemainingOptions(options);
}
开发者ID:dsibournemouth，项目名称:autoweka，代码行数:58，代码来源:HierarchicalClusterer.java
示例16: setDistanceFunction
import weka.core.DistanceFunction; //导入依赖的package包/类
/**
* Sets the distance function to use for nearest neighbour search.
* Currently only EuclideanDistance is supported.
*
* @param df the distance function to use
* @throws Exception if not EuclideanDistance
*/
public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance))
throw new Exception("CoverTree currently only works with "
+ "EuclideanDistanceFunction.");
m_DistanceFunction = m_EuclideanDistance = (EuclideanDistance) df;
}
开发者ID:dsibournemouth，项目名称:autoweka，代码行数:14，代码来源:CoverTree.java
注：本文中的weka.core.DistanceFunction类示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。 |
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