package org.data2semantics.exp.ecml2013;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
import org.data2semantics.exp.RDFMLExperiment;
import org.data2semantics.exp.old.utils.Experimenter;
import org.data2semantics.exp.old.utils.datasets.DataSetFactory;
import org.data2semantics.exp.old.utils.datasets.GeneralPredictionDataSetParameters;
import org.data2semantics.exp.old.utils.datasets.PropertyPredictionDataSet;
import org.data2semantics.exp.utils.GraphKernelExperiment;
import org.data2semantics.exp.utils.GraphKernelRunTimeExperiment;
import org.data2semantics.exp.utils.KernelExperiment;
import org.data2semantics.exp.utils.RDFKernelRunTimeExperiment;
import org.data2semantics.exp.utils.RDFOldKernelExperiment;
import org.data2semantics.exp.utils.Result;
import org.data2semantics.exp.utils.ResultsTable;
import org.data2semantics.proppred.kernels.graphkernels.GraphKernel;
import org.data2semantics.proppred.kernels.rdfgraphkernels.RDFGraphKernel;
import org.data2semantics.proppred.kernels.rdfgraphkernels.RDFIntersectionPartialSubTreeKernel;
import org.data2semantics.proppred.kernels.rdfgraphkernels.RDFIntersectionSubTreeKernel;
import org.data2semantics.proppred.learners.libsvm.LibSVM;
import org.data2semantics.proppred.learners.libsvm.LibSVMParameters;
import org.data2semantics.tools.rdf.RDFFileDataSet;
import org.openrdf.model.Resource;
import org.openrdf.model.Statement;
import org.openrdf.model.Value;
import org.openrdf.rio.RDFFormat;
/**
* Class for running the three experiments in the ECML 2013 paper: de Vries, G.K.D. "A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data" on the BGS dataset.
* The class contains a main method with the optional -file parameter to provide the directory of the BGS dataset (without the file names).
*
* @author Gerben
*
*/
public class GeoCompareExperiment extends RDFMLExperiment {
private static String dataDir = "C:\\Users\\Gerben\\Dropbox\\data_bgs_ac_uk_ALL";
/**
* Run the three experiments for the BGS dataset
*
* @param args
*/
public static void main(String[] args) {
// parse location of the data
for (int i = 0; i < args.length; i++) {
if (args[i].equals("-file")) {
i++;
dataDir = args[i];
}
}
// The lithogenesis prediction task
lithogenesisExperiments();
// The run time of the lithogenesis prediction task
lithogenesisRunningTimeExperiments();
// the prediction task for the geological theme (this one is slow)
themeExperiments(0.1, 50);
}
private static void lithogenesisRunningTimeExperiments() {
dataset = new RDFFileDataSet(dataDir, RDFFormat.NTRIPLES);
double[] fractions = {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1};
double[] cs = {1}; // dummy, we don't care about the prediction scores
long[] seeds = {11,21,31,41,51,61,71,81,91,101};
//long[] seeds = {11};
int depth = 3;
int iteration = 6;
boolean inference = true;
LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
ResultsTable resTable = new ResultsTable();
resTable.newRow("WL RDF");
for (double frac : fractions) {
Result res = new Result();
res.setLabel("runtime");
for (long seed : seeds) {
createGeoDataSet(seed,frac,6,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
KernelExperiment<RDFGraphKernel> exp = new RDFKernelRunTimeExperiment(new ECML2013RDFWLSubTreeKernel(iteration, depth, inference, true, false), seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running WL RDF: " + frac);
exp.run();
res.addResult(exp.getResults().get(0));
}
resTable.addResult(res);
}
resTable.newRow("IST");
for (double frac : fractions) {
Result res = new Result();
res.setLabel("runtime");
for (long seed : seeds) {
createGeoDataSet(seed,frac,6,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
KernelExperiment<RDFGraphKernel> exp = new RDFKernelRunTimeExperiment(new RDFIntersectionSubTreeKernel(depth, 1, inference, true, false), seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running IST: " + frac);
exp.run();
res.addResult(exp.getResults().get(0));
}
resTable.addResult(res);
}
long tic, toc;
resTable.newRow("WL");
for (double frac : fractions) {
Result res = new Result();
res.setLabel("runtime");
for (long seed : seeds) {
createGeoDataSet(seed,frac,6,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
tic = System.currentTimeMillis();
PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
toc = System.currentTimeMillis();
KernelExperiment<GraphKernel> exp = new GraphKernelRunTimeExperiment(new ECML2013WLSubTreeKernel(iteration), seeds, parms, ds.getGraphs(), labels);
System.out.println("Running WL: " + frac);
exp.run();
res.addResult(exp.getResults().get(0));
double[] comps = {2 * (toc-tic) + res.getScore()};
Result resC = new Result(comps,"comp time 2");
res.addResult(resC);
}
resTable.addResult(res);
}
/*
resTable.newRow("");
for (double frac : fractions) {
createGeoDataSet(11,frac,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
tic = System.currentTimeMillis();
PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
toc = System.currentTimeMillis();
KernelExperiment<GraphKernel> exp = new GraphKernelExperiment(new ECML2013IntersectionGraphPathKernel(2,1), seeds, parms, ds.getGraphs(), labels);
System.out.println("Running IGP: " + frac);
exp.run();
double[] comps = {0,0};
comps[0] = 2*(toc-tic) + exp.getResults().get(exp.getResults().size()-1).getScore();
comps[1] = 2*(toc-tic) + exp.getResults().get(exp.getResults().size()-1).getScore();
Result resC = new Result(comps,"comp time 2");
exp.getResults().get(exp.getResults().size()-1).addResult(resC);
resTable.addResult(exp.getResults().get(exp.getResults().size()-1));
}
*/
resTable.newRow("IGW");
for (double frac : fractions) {
Result res = new Result();
res.setLabel("runtime");
for (long seed : seeds) {
createGeoDataSet(seed,frac,6,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
tic = System.currentTimeMillis();
PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
toc = System.currentTimeMillis();
KernelExperiment<GraphKernel> exp = new GraphKernelRunTimeExperiment(new ECML2013IntersectionGraphWalkKernel(2,1), seeds, parms, ds.getGraphs(), labels);
System.out.println("Running IGW: " + frac);
exp.run();
res.addResult(exp.getResults().get(0));
double[] comps = {2 * (toc-tic) + res.getScore()};
Result resC = new Result(comps,"comp time 2");
res.addResult(resC);
}
resTable.addResult(res);
}
//resTable.addCompResults(resTable.getBestResults());
System.out.println(resTable);
saveResults(resTable.toString(), "lithogenesis_runningtime.txt");
}
private static void themeExperiments(double fraction, int minSize) {
long[] seeds = {11,21,31,41,51,61,71,81,91,101};
double[] cs = {0.001, 0.01, 0.1, 1, 10, 100, 1000};
int depth = 3;
int[] iterations = {0, 2, 4, 6};
dataset = new RDFFileDataSet(dataDir, RDFFormat.NTRIPLES);
LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
ResultsTable resTable = new ResultsTable();
resTable.setManWU(0.05);
boolean inference = false;
for (int i = 1; i <= depth; i++) {
resTable.newRow("WL RDF, no inference, depth="+i);
for (int it : iterations) {
Experimenter experimenter = new Experimenter(2);
Thread expT = new Thread(experimenter);
expT.setDaemon(true);
expT.start();
List<List<Result>> res = new ArrayList<List<Result>>();
for (long seed : seeds) {
long[] s2 = new long[1];
s2[0] = seed;
createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new ECML2013RDFWLSubTreeKernel(it, i, inference, true, false), s2, parms, dataset, instances, labels, blackList);
res.add(exp.getResults());
System.out.println("Running WL RDF: " + i + " " + it);
if (experimenter.hasSpace()) {
experimenter.addExperiment(exp);
}
}
experimenter.stop();
try {
while (expT.isAlive()) {
Thread.sleep(1000);
}
} catch (Exception e) {
e.printStackTrace();
}
for (Result res2 : Result.mergeResultLists(res)) {
resTable.addResult(res2);
}
}
}
saveResults(resTable, "geo_theme.ser");
inference = true;
for (int i = 1; i <= depth; i++) {
resTable.newRow("WL RDF, inference, depth="+i);
for (int it : iterations) {
Experimenter experimenter = new Experimenter(2);
Thread expT = new Thread(experimenter);
expT.setDaemon(true);
expT.start();
List<List<Result>> res = new ArrayList<List<Result>>();
for (long seed : seeds) {
long[] s2 = new long[1];
s2[0] = seed;
createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new ECML2013RDFWLSubTreeKernel(it, i, inference, true, false), s2, parms, dataset, instances, labels, blackList);
res.add(exp.getResults());
System.out.println("Running WL RDF: " + i + " " + it);
if (experimenter.hasSpace()) {
experimenter.addExperiment(exp);
}
}
experimenter.stop();
while (expT.isAlive()) {
try {
Thread.sleep(1000);
} catch (Exception e) {
e.printStackTrace();
}
}
for (Result res2 : Result.mergeResultLists(res)) {
resTable.addResult(res2);
}
}
}
saveResults(resTable, "geo_theme.ser");
inference = false;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IST, no inference, depth="+i);
Experimenter experimenter = new Experimenter(2);
Thread expT = new Thread(experimenter);
expT.setDaemon(true);
expT.start();
List<List<Result>> res = new ArrayList<List<Result>>();
for (long seed : seeds) {
long[] s2 = new long[1];
s2[0] = seed;
createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true, false), s2, parms, dataset, instances, labels, blackList);
res.add(exp.getResults());
System.out.println("Running IST: " + i);
if (experimenter.hasSpace()) {
experimenter.addExperiment(exp);
}
}
experimenter.stop();
while (expT.isAlive()) {
try {
Thread.sleep(1000);
} catch (Exception e) {
e.printStackTrace();
}
}
for (Result res2 : Result.mergeResultLists(res)) {
resTable.addResult(res2);
}
}
saveResults(resTable, "geo_theme.ser");
inference = true;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IST, inference, depth="+i);
Experimenter experimenter = new Experimenter(2);
Thread expT = new Thread(experimenter);
expT.setDaemon(true);
expT.start();
List<List<Result>> res = new ArrayList<List<Result>>();
for (long seed : seeds) {
long[] s2 = new long[1];
s2[0] = seed;
createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true, false), s2, parms, dataset, instances, labels, blackList);
res.add(exp.getResults());
System.out.println("Running IST: " + i);
if (experimenter.hasSpace()) {
experimenter.addExperiment(exp);
}
}
experimenter.stop();
while (expT.isAlive()) {
try {
Thread.sleep(1000);
} catch (Exception e) {
e.printStackTrace();
}
}
for (Result res2 : Result.mergeResultLists(res)) {
resTable.addResult(res2);
}
}
saveResults(resTable, "geo_theme.ser");
inference = false;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IPST, no inference, depth="+i);
Experimenter experimenter = new Experimenter(2);
Thread expT = new Thread(experimenter);
expT.setDaemon(true);
expT.start();
List<List<Result>> res = new ArrayList<List<Result>>();
for (long seed : seeds) {
long[] s2 = new long[1];
s2[0] = seed;
createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionPartialSubTreeKernel(i, 0.01, inference, true, false), s2, parms, dataset, instances, labels, blackList);
res.add(exp.getResults());
System.out.println("Running IPST: " + i);
if (experimenter.hasSpace()) {
experimenter.addExperiment(exp);
}
}
experimenter.stop();
while (expT.isAlive()) {
try {
Thread.sleep(1000);
} catch (Exception e) {
e.printStackTrace();
}
}
for (Result res2 : Result.mergeResultLists(res)) {
resTable.addResult(res2);
}
}
saveResults(resTable, "geo_theme.ser");
inference = true;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IPST, inference, depth="+i);
Experimenter experimenter = new Experimenter(2);
Thread expT = new Thread(experimenter);
expT.setDaemon(true);
expT.start();
List<List<Result>> res = new ArrayList<List<Result>>();
for (long seed : seeds) {
long[] s2 = new long[1];
s2[0] = seed;
createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionPartialSubTreeKernel(i, 0.01, inference, true, false), s2, parms, dataset, instances, labels, blackList);
res.add(exp.getResults());
System.out.println("Running IPST: " + i);
if (experimenter.hasSpace()) {
experimenter.addExperiment(exp);
}
}
experimenter.stop();
while (expT.isAlive()) {
try {
Thread.sleep(1000);
} catch (Exception e) {
e.printStackTrace();
}
}
for (Result res2 : Result.mergeResultLists(res)) {
resTable.addResult(res2);
}
}
saveResults(resTable, "geo_theme.ser");
resTable.addCompResults(resTable.getBestResults());
System.out.println(resTable);
saveResults(resTable.toString(), "geo_theme" + fraction + ".txt");
}
private static void lithogenesisExperiments() {
long[] seeds = {11,21,31,41,51,61,71,81,91,101};
double[] cs = {0.001, 0.01, 0.1, 1, 10, 100, 1000};
int depth = 3;
int[] iterations = {0, 2, 4, 6};
boolean blankLabels = false;
dataset = new RDFFileDataSet(dataDir, RDFFormat.NTRIPLES);
createGeoDataSet(1, 1, "http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
//parms.setEvalFunction(LibSVM.F1);
ResultsTable resTable = new ResultsTable();
resTable.setDigits(2);
boolean inference = false;
for (int i = 1; i <= depth; i++) {
resTable.newRow("WL RDF, no inference, depth="+i);
for (int it : iterations) {
ECML2013RDFWLSubTreeKernel k = new ECML2013RDFWLSubTreeKernel(it, i, inference, true, blankLabels);
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(k, seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running WL RDF: " + i + " " + it);
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
}
}
saveResults(resTable, "geo_litho.ser");
inference = true;
for (int i = 1; i <= depth; i++) {
resTable.newRow("WL RDF, inference, depth="+i);
for (int it : iterations) {
ECML2013RDFWLSubTreeKernel k = new ECML2013RDFWLSubTreeKernel(it, i, inference, true, blankLabels);
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(k, seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running WL RDF: " + i + " " + it);
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
}
}
saveResults(resTable, "geo_litho.ser");
inference = false;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IST, no inference, depth="+i);
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true, blankLabels), seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running IST: " + i + " ");
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
}
saveResults(resTable, "geo_litho.ser");
inference = true;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IST, inference, depth="+i);
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true, blankLabels), seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running IST: " + i + " ");
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
}
saveResults(resTable, "geo_litho.ser");
inference = false;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IPST, no inference, depth="+i);
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionPartialSubTreeKernel(i, 0.01, inference, true, blankLabels), seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running IPST: " + i + " ");
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
}
saveResults(resTable, "geo_litho.ser");
inference = true;
for (int i = 1; i <= depth; i++) {
resTable.newRow("IPST, inference, depth="+i);
KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionPartialSubTreeKernel(i, 0.01, inference, true, blankLabels), seeds, parms, dataset, instances, labels, blackList);
System.out.println("Running IPST: " + i + " ");
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
}
saveResults(resTable, "geo_litho.ser");
List<GeneralPredictionDataSetParameters> dataSetsParams = new ArrayList<GeneralPredictionDataSetParameters>();
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, false));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, false));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, false));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, true));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, true));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
int[] iterationsIG = {1,2};
long tic, toc;
for (GeneralPredictionDataSetParameters params : dataSetsParams) {
tic = System.currentTimeMillis();
PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(params);
toc = System.currentTimeMillis();
if (blankLabels) {
ds.removeVertexAndEdgeLabels();
}
resTable.newRow("WL");
for (int it : iterations) {
KernelExperiment<GraphKernel> exp = new GraphKernelExperiment(new ECML2013WLSubTreeKernel(it), seeds, parms, ds.getGraphs(), labels);
System.out.println("Running WL: " + it);
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
double[] comps = {0,0};
comps[0] = toc-tic;
comps[1] = toc-tic;
Result resC = new Result(comps,"comp time 2");
resTable.addResult(resC);
}
}
saveResults(resTable, "geo_litho.ser");
/*
dataSetsParams = new ArrayList<GeneralPredictionDataSetParameters>();
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, false));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, false));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, true));
dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, true));
*/
for (GeneralPredictionDataSetParameters params : dataSetsParams) {
tic = System.currentTimeMillis();
PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(params);
toc = System.currentTimeMillis();
if (blankLabels) {
ds.removeVertexAndEdgeLabels();
}
resTable.newRow("IGP");
for (int it : iterationsIG) {
KernelExperiment<GraphKernel> exp = new GraphKernelExperiment(new ECML2013IntersectionGraphPathKernel(it,1), seeds, parms, ds.getGraphs(), labels);
System.out.println("Running IGP: " + it);
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
double[] comps = {0,0};
comps[0] = toc-tic;
comps[1] = toc-tic;
Result resC = new Result(comps,"comp time 2");
resTable.addResult(resC);
}
}
saveResults(resTable, "geo_litho.ser");
for (GeneralPredictionDataSetParameters params : dataSetsParams) {
tic = System.currentTimeMillis();
PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(params);
toc = System.currentTimeMillis();
if (blankLabels) {
ds.removeVertexAndEdgeLabels();
}
resTable.newRow("IGW");
for (int it : iterationsIG) {
KernelExperiment<GraphKernel> exp = new GraphKernelExperiment(new ECML2013IntersectionGraphWalkKernel(it,1), seeds, parms, ds.getGraphs(), labels);
System.out.println("Running IGW: " + it);
exp.run();
for (Result res : exp.getResults()) {
resTable.addResult(res);
}
double[] comps = {0,0};
comps[0] = toc-tic;
comps[1] = toc-tic;
Result resC = new Result(comps,"comp time 2");
resTable.addResult(resC);
}
}
saveResults(resTable, "geo_litho.ser");
resTable.addCompResults(resTable.getBestResults());
System.out.println(resTable);
saveResults(resTable.toString(), "geo_litho.txt");
}
private static void createGeoDataSet(long seed, double fraction, String property) {
createGeoDataSet(seed, fraction, 10, property);
}
private static void createGeoDataSet(long seed, double fraction, int minSize, String property) {
String majorityClass = "http://data.bgs.ac.uk/id/Lexicon/Class/LS";
Random rand = new Random(seed);
List<Statement> stmts = dataset.getStatementsFromStrings(null, "http://www.w3.org/2000/01/rdf-schema#isDefinedBy", "http://data.bgs.ac.uk/ref/Lexicon/NamedRockUnit");
System.out.println(dataset.getLabel());
System.out.println("Component Rock statements: " + stmts.size());
instances = new ArrayList<Resource>();
labels = new ArrayList<Value>();
blackList = new ArrayList<Statement>();
// http://data.bgs.ac.uk/ref/Lexicon/hasRockUnitRank
// http://data.bgs.ac.uk/ref/Lexicon/hasTheme
for(Statement stmt: stmts) {
List<Statement> stmts2 = dataset.getStatementsFromStrings(stmt.getSubject().toString(), property, null);
if (stmts2.size() > 1) {
System.out.println("more than 1 Class");
}
for (Statement stmt2 : stmts2) {
if (rand.nextDouble() <= fraction) {
instances.add(stmt2.getSubject());
labels.add(stmt2.getObject());
/*
if (stmt2.getObject().toString().equals(majorityClass)) {
labels.add(ds.createLiteral("pos"));
} else {
labels.add(ds.createLiteral("neg"));
}
*/
}
}
}
//capClassSize(50, seed);
removeSmallClasses(minSize);
createBlackList();
Map<Value, Integer> labelMap = new HashMap<Value, Integer>();
System.out.println(LibSVM.computeClassCounts(LibSVM.createTargets(labels, labelMap)));
System.out.println(labelMap);
}
}