use of edu.neu.ccs.pyramid.optimization.LBFGS in project pyramid by cheng-li.
the class CMLCRFTest method test9.
private static void test9() {
MultiLabelClfDataSet train = MultiLabelSynthesizer.independentNoise();
MultiLabelClfDataSet test = MultiLabelSynthesizer.independent();
CMLCRF cmlcrf = new CMLCRF(train);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(0).set(0, 0);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(0).set(1, 1);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(1).set(0, 1);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(1).set(1, 1);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(2).set(0, 1);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(2).set(1, 0);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(3).set(0, 1);
cmlcrf.getWeights().getWeightsWithoutBiasForClass(3).set(1, -1);
CRFLoss crfLoss = new CRFLoss(cmlcrf, train, 1);
System.out.println(cmlcrf);
System.out.println("initial loss = " + crfLoss.getValue());
System.out.println("training performance");
System.out.println(new MLMeasures(cmlcrf, train));
System.out.println("test performance");
System.out.println(new MLMeasures(cmlcrf, test));
LBFGS optimizer = new LBFGS(crfLoss);
while (!optimizer.getTerminator().shouldTerminate()) {
System.out.println("------------");
optimizer.iterate();
System.out.println(optimizer.getTerminator().getLastValue());
System.out.println("training performance");
System.out.println(new MLMeasures(cmlcrf, train));
System.out.println("test performance");
System.out.println(new MLMeasures(cmlcrf, test));
}
System.out.println(cmlcrf);
}
use of edu.neu.ccs.pyramid.optimization.LBFGS in project pyramid by cheng-li.
the class CMLCRFTest method test6.
private static void test6() throws Exception {
MultiLabelClfDataSet dataSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "medical/train"), DataSetType.ML_CLF_SPARSE, true);
MultiLabelClfDataSet testSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "medical/test"), DataSetType.ML_CLF_SPARSE, true);
CMLCRF cmlcrf = new CMLCRF(dataSet);
CRFLoss crfLoss = new CRFLoss(cmlcrf, dataSet, 1);
MultiLabel[] predTrain;
MultiLabel[] predTest;
LBFGS optimizer = new LBFGS(crfLoss);
for (int i = 0; i < 50; i++) {
// System.out.print("Obj: " + optimizer.getTerminator().getLastValue());
System.out.println("iter: " + i);
optimizer.iterate();
System.out.println(crfLoss.getValue());
predTrain = cmlcrf.predict(dataSet);
predTest = cmlcrf.predict(testSet);
System.out.print("\tTrain acc: " + Accuracy.accuracy(dataSet.getMultiLabels(), predTrain));
System.out.print("\tTrain overlap " + Overlap.overlap(dataSet.getMultiLabels(), predTrain));
System.out.print("\tTest acc: " + Accuracy.accuracy(testSet.getMultiLabels(), predTest));
System.out.println("\tTest overlap " + Overlap.overlap(testSet.getMultiLabels(), predTest));
// System.out.println("crf = "+cmlcrf.getWeights());
// System.out.println(Arrays.toString(predTrain));
}
}
use of edu.neu.ccs.pyramid.optimization.LBFGS in project pyramid by cheng-li.
the class CMLCRFTest method test1.
private static void test1() throws Exception {
MultiLabelClfDataSet dataSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "spam/trec_data/train.trec"), DataSetType.ML_CLF_SPARSE, true);
MultiLabelClfDataSet testSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "spam/trec_data/test.trec"), DataSetType.ML_CLF_SPARSE, true);
CMLCRF cmlcrf = new CMLCRF(dataSet);
CRFLoss crfLoss = new CRFLoss(cmlcrf, dataSet, 1);
cmlcrf.setConsiderPair(true);
MultiLabel[] predTrain;
MultiLabel[] predTest;
LBFGS optimizer = new LBFGS(crfLoss);
for (int i = 0; i < 5000; i++) {
// System.out.print("Obj: " + optimizer.getTerminator().getLastValue());
System.out.println("iter: " + i);
optimizer.iterate();
System.out.println(crfLoss.getValue());
predTrain = cmlcrf.predict(dataSet);
predTest = cmlcrf.predict(testSet);
System.out.print("\tTrain acc: " + Accuracy.accuracy(dataSet.getMultiLabels(), predTrain));
System.out.print("\tTrain overlap " + Overlap.overlap(dataSet.getMultiLabels(), predTrain));
System.out.print("\tTest acc: " + Accuracy.accuracy(testSet.getMultiLabels(), predTest));
System.out.println("\tTest overlap " + Overlap.overlap(testSet.getMultiLabels(), predTest));
// System.out.println("crf = "+cmlcrf.getWeights());
// System.out.println(Arrays.toString(predTrain));
}
// LBFGS optimizer = new LBFGS(crfLoss);
// optimizer.getTerminator().setAbsoluteEpsilon(0.01);
// optimizer.optimize();
// predTrain = cmlcrf.predict(dataSet);
// predTest = cmlcrf.predict(testSet);
// System.out.print("Train acc: " + Accuracy.accuracy(dataSet.getMultiLabels(), predTrain));
// System.out.print("\tTrain overlap " + Overlap.overlap(dataSet.getMultiLabels(), predTrain));
// System.out.print("\tTest acc: " + Accuracy.accuracy(testSet.getMultiLabels(), predTest));
// System.out.println("\tTest overlap " + Overlap.overlap(testSet.getMultiLabels(), predTest));
}
use of edu.neu.ccs.pyramid.optimization.LBFGS in project pyramid by cheng-li.
the class CMLCRFTest method test4.
private static void test4() throws Exception {
MultiLabelClfDataSet dataSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "20newsgroup/1/train.trec"), DataSetType.ML_CLF_SPARSE, true);
MultiLabelClfDataSet testSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "20newsgroup/1/test.trec"), DataSetType.ML_CLF_SPARSE, true);
CMLCRF cmlcrf = new CMLCRF(dataSet);
CRFLoss crfLoss = new CRFLoss(cmlcrf, dataSet, 1);
MultiLabel[] predTrain;
MultiLabel[] predTest;
LBFGS optimizer = new LBFGS(crfLoss);
for (int i = 0; i < 50; i++) {
// System.out.print("Obj: " + optimizer.getTerminator().getLastValue());
System.out.println("iter: " + i);
optimizer.iterate();
System.out.println(crfLoss.getValue());
predTrain = cmlcrf.predict(dataSet);
predTest = cmlcrf.predict(testSet);
System.out.print("\tTrain acc: " + Accuracy.accuracy(dataSet.getMultiLabels(), predTrain));
System.out.print("\tTrain overlap " + Overlap.overlap(dataSet.getMultiLabels(), predTrain));
System.out.print("\tTest acc: " + Accuracy.accuracy(testSet.getMultiLabels(), predTest));
System.out.println("\tTest overlap " + Overlap.overlap(testSet.getMultiLabels(), predTest));
// System.out.println("crf = "+cmlcrf.getWeights());
// System.out.println(Arrays.toString(predTrain));
}
}
use of edu.neu.ccs.pyramid.optimization.LBFGS in project pyramid by cheng-li.
the class LogisticRegressionTest method test3.
private static void test3() throws Exception {
ClfDataSet dataSet = TRECFormat.loadClfDataSet(new File(DATASETS, "/imdb/3/train.trec"), DataSetType.CLF_SPARSE, false);
ClfDataSet testSet = TRECFormat.loadClfDataSet(new File(DATASETS, "/imdb/3/test.trec"), DataSetType.CLF_SPARSE, false);
System.out.println(dataSet.getMetaInfo());
LogisticRegression logisticRegression = new LogisticRegression(dataSet.getNumClasses(), dataSet.getNumFeatures());
LogisticLoss function = new LogisticLoss(logisticRegression, dataSet, 0.1, true);
LBFGS lbfgs = new LBFGS(function);
lbfgs.optimize();
System.out.println("train: " + Accuracy.accuracy(logisticRegression, dataSet));
System.out.println("test: " + Accuracy.accuracy(logisticRegression, testSet));
}
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