本文整理了Java中org.deeplearning4j.nn.multilayer.MultiLayerNetwork.evaluate()方法的一些代码示例，展示了MultiLayerNetwork.evaluate()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。MultiLayerNetwork.evaluate()方法的具体详情如下：
包路径：org.deeplearning4j.nn.multilayer.MultiLayerNetwork
类名称：MultiLayerNetwork
方法名：evaluate

MultiLayerNetwork.evaluate介绍

[英]Evaluate the network (classification performance)
[中]评估网络（分类性能）

代码示例

代码示例来源：origin: deeplearning4j/dl4j-examples

Evaluation eval = network.evaluate(validateIterator);
log.info(eval.stats(true));

代码示例来源：origin: deeplearning4j/dl4j-examples

Evaluation evaluation = net.evaluate(test);
System.out.println(evaluation.stats());

代码示例来源：origin: org.deeplearning4j/arbiter-deeplearning4j

/**
 *
 * @param model
 * @param testData
 * @return
 */
public static Evaluation getEvaluation(MultiLayerNetwork model, DataSetIterator testData) {
  return model.evaluate(testData);
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

/**
 * Evaluate the network (classification performance)
 *
 * @param iterator Iterator to evaluate on
 * @return Evaluation object; results of evaluation on all examples in the data set
 */
public Evaluation evaluate(DataSetIterator iterator) {
  return evaluate(iterator, null);
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

/**
 * Evaluate the network on the provided data set. Used for evaluating the performance of classifiers
 *
 * @param iterator Data to undertake evaluation on
 * @return Evaluation object, summarizing the results of the evaluation on the provided DataSetIterator
 */
public Evaluation evaluate(DataSetIterator iterator, List<String> labelsList) {
  return evaluate(iterator, labelsList, 1);
}

代码示例来源：origin: sjsdfg/dl4j-tutorials

@Override
public double calculateScore(MultiLayerNetwork network) {
  double sum = 0;
  for (DataSetIterator dataSetIterator : dataSetIterators) {
    Evaluation eval = network.evaluate(dataSetIterator);
    sum += eval.accuracy();
  }
  return sum / dataSetIterators.length;
}

代码示例来源：origin: org.deeplearning4j/arbiter-deeplearning4j

@Override
public double score(MultiLayerNetwork net, DataSetIterator iterator) {
  Evaluation e = net.evaluate(iterator);
  return e.f1();
}

代码示例来源：origin: org.deeplearning4j/arbiter-deeplearning4j

@Override
public double score(MultiLayerNetwork net, DataSetIterator iterator) {
  Evaluation e = net.evaluate(iterator);
  return e.accuracy();
}

代码示例来源：origin: mccorby/FederatedAndroidTrainer

@Override
public String evaluate(FederatedDataSet federatedDataSet) {
  DataSet testData = (DataSet) federatedDataSet.getNativeDataSet();
  List<DataSet> listDs = testData.asList();
  DataSetIterator iterator = new ListDataSetIterator(listDs, BATCH_SIZE);
  return mNetwork.evaluate(iterator).stats();
}

代码示例来源：origin: sjsdfg/dl4j-tutorials

Evaluation eval = model.evaluate(mnistTest);
log.info(eval.stats());
mnistTest.reset();

代码示例来源：origin: sjsdfg/dl4j-tutorials

DataSetIterator testIterator = new RecordReaderDataSetIterator(testReader, batchSize, 1, numLabels);
testIterator.setPreProcessor(scaler);
Evaluation eval = network.evaluate(testIterator);

代码示例来源：origin: rahul-raj/Deeplearning4J

Evaluation evaluation = model.evaluate(splitter.getTestIterator(),Arrays.asList("0","1"));
System.out.println("args = " + evaluation.stats() + "");

代码示例来源：origin: tahaemara/arabic-characters-recognition

Evaluation eval = model.evaluate(titerator);
log.info(eval.stats(true));

代码示例来源：origin: rahul-raj/Deeplearning4J

dataSetIterator.setPreProcessor(scaler);
Evaluation evaluation = model.evaluate(dataSetIterator);
System.out.println("args = [" + evaluation.stats() + "]");