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ImageJ ImageJ can be used to extract features from images. ImageJ contains a macro language with which it is easy to extract features and then dump them into an ARFF file. Links ImageJ homepage
.core.converters.ConverterUtils.DataSource import java.util.Random /** * Determines the best class-weights for LibSVM from a list of weight strings. * <p/> * Just runs LibSVM on a binary dataset and chooses the class-weights * with the best ... .size() == 0) { println "Usage: LibsvmWeights.groovy <ARFF-file>" return; } // load data data = Data
(in that case the last * attribute), adds some test weights and saves it as XRFF file * under "args[1]". E.g.: <br/> * AddWeights anneal.arff anneal.xrff.gz * * @author FracPete (fracpete at waikato dot ac dot nz) */ public class AddWeights { public static void main(String[] args) throws
The following examples show how to add weights to normal datasets and save them in the new XRFF ... for this code to work. Add arbitrary weights import weka ... weights and saves it as XRFF file * under "args[1]". E.g.: <br/> * AddWeights anneal.arff anneal
.core.converters.XRFFSaver; import weka.core.Instances; import java.io.File; /** * Loads file "args[0]", Adds weight given ... the last * attribute) and saves it as XRFF file * under "args[2]". E.g.: <br/> * AddWeights ... 23 at waikato dot ac dot nz) */ public class AddWeightsFromAtt { public static void main
attribute), adds weights from "args[1]" (one weight * per line) and saves it as XRFF file under "args[2]". E.g.: <br/> * AddWeightsFromFile anneal.arff weights.txt anneal.xrff.gz * * @author FracPete (fracpete at waikato dot ac dot nz) */ public class AddWeightsFromFile { public static void main
*)> <!ATTLIST instance type (normal|sparse) "normal"> <!ATTLIST instance weight CDATA #IMPLIED ... and uncompressed XRFF files (this applies also to ARFF files). Additional features In addition to all the features of the ARFF format, the XRFF format contains the following additional features: class attribute
http://weka.wikispaces.com/XRFF - last edited Aug 6, 2009 by fracpete fracpete
|| We != Ne) { // weighted counts + text.append(" ("+Utils.roundDouble(W,2)); + if (Utils ... /classifiers/trees/j48/Distribution.java 2005-08-05 14:23:08.000000000 +0000 @@ -46,6 +46,18 @@ /** Total weight ... { int i, j; + if (true) throw new Exception("Constructor won't handle weights."); m
Description J48-Weighter patch: Modification of J48 for Weighted Data. Reference -none ... as an instance weight. As mentioned on Wekalist, tests using weighted sample-survey data indicated possible ... Weighter is a general-purpose filter independent of J48 or other classifiers, but to preserve the weight
@cs.waikato.ac.nz) * @version $Revision: 1.11 $ */ public class ZeroR extends Classifier implements Weighted ... { double sumOfWeights = 0; m_Class = instances.classAttribute(); m_ClassValue = 0; switch ... < m_Counts.length; i++) { m_Counts[i] = 1; } sumOfWeights = instances
of Java but has additional power features inspired by languages like Python, Ruby and Smalltalk makes modern programming features available to Java developers with almost-zero learning curve supports Domain ... GeroR extends Classifier implements WeightedInstancesHandler { ... } For more information
.core.RevisionUtils import weka.core.Utils import weka.core.WeightedInstancesHandler import weka ... ) * @version $Revision$ */ class GeroR extends Classifier implements Weighted ... .deleteWithMissingClass() double sumOfWeights = 0 m_Class = instances.classAttribute() m_ClassValue = 0 switch
.deleteWithMissingClass() sumOfWeights = 0 self.__Class = instances.classAttribute() self ... (len(self.__Counts)): self.__Counts[i] = 1 sumOfWeights = instances.numClasses() enu = instances ... .__Counts[int(instance.classValue())] += instance.weight() else: self.__ClassValue += instance.weight
and saved as Sparse ARFF files. Instance weights in ARFF files This feature exists in versions of Weka >= 3.5.8. A weight can be associated with an instance in a standard ARFF file by appending ... "class A"}, {5} Note that any instance without a weight value specified is assumed to have a weight of 1
and saved as Sparse ARFF files. Instance weights in ARFF files This feature exists in versions of Weka >= 3.5.8. A weight can be associated with an instance in a standard ARFF file by appending ... "class A"}, {5} Note that any instance without a weight value specified is assumed to have a weight of 1
?combining?a?large?set?of?diverse?models?in?to?a?high? performance?ensemble?by?determining?appropriate?weights?for?the?models.??The?algorithm was?inspired?by?forward?stepwise?feature?selection,?wherein?features?are?added?one?at?a time?to ... ?performance?the?most?on?the?validation?data.??When?we?are?done,?we?can consider?the?number?of?times?a?model?was?added?as?its??weight
Prospectr uses the ADTree algorithm from Weka to classify genes as likely or unlikely to be involved in human hereditary disease, based on features derived from their sequence. External links Prospectr homepage
http://weka.wikispaces.com/Prospectr - last edited Aug 1, 2009 by weka weka
of instances (weight of instances) reaching the leaf. The second number is the number (weight) of those
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Mac OS X 10.8 (Mountain Lion) introduced a new security feature that, by default, limits "acceptable" applications to only those downloaded from the Mac App store. Thankfully, you can alter this in the system preferences. Go to "Security & Privacy" and change the "Allow applications downloaded from