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Java NominalMapping.getPositiveString方法代碼示例

本文整理匯總了Java中com.rapidminer.example.table.NominalMapping.getPositiveString方法的典型用法代碼示例。如果您正苦於以下問題：Java NominalMapping.getPositiveString方法的具體用法？Java NominalMapping.getPositiveString怎麽用？Java NominalMapping.getPositiveString使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類com.rapidminer.example.table.NominalMapping的用法示例。


在下文中一共展示了NominalMapping.getPositiveString方法的5個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Java代碼示例。

示例1: learn

import com.rapidminer.example.table.NominalMapping; //導入方法依賴的package包/類
@Override
public Model learn(ExampleSet exampleSet) throws OperatorException {
	Kernel kernel = getKernel();
	kernel.init(exampleSet);

	double initLearnRate = getParameterAsDouble(PARAMETER_LEARNING_RATE);
	NominalMapping labelMapping = exampleSet.getAttributes().getLabel().getMapping();
	String classNeg = labelMapping.getNegativeString();
	String classPos = labelMapping.getPositiveString();
	double classValueNeg = labelMapping.getNegativeIndex();
	int numberOfAttributes = exampleSet.getAttributes().size();
	HyperplaneModel model = new HyperplaneModel(exampleSet, classNeg, classPos, kernel);
	model.init(new double[numberOfAttributes], 0);
	for (int round = 0; round <= getParameterAsInt(PARAMETER_ROUNDS); round++) {
		double learnRate = getLearnRate(round, getParameterAsInt(PARAMETER_ROUNDS), initLearnRate);
		Attributes attributes = exampleSet.getAttributes();
		for (Example example : exampleSet) {
			double prediction = model.predict(example);
			if (prediction != example.getLabel()) {
				double direction = (example.getLabel() == classValueNeg) ? -1 : 1;
				// adapting intercept
				model.setIntercept(model.getIntercept() + learnRate * direction);
				// adapting coefficients
				double coefficients[] = model.getCoefficients();
				int i = 0;
				for (Attribute attribute : attributes) {
					coefficients[i] += learnRate * direction * example.getValue(attribute);
					i++;
				}
			}
		}
	}
	return model;
}
開發者ID:transwarpio，項目名稱:rapidminer，代碼行數:35，代碼來源:Perceptron.java

示例2: learn

import com.rapidminer.example.table.NominalMapping; //導入方法依賴的package包/類
@Override
public Model learn(ExampleSet exampleSet) throws OperatorException {
	Kernel kernel = getKernel();

	double initLearnRate = getParameterAsDouble(PARAMETER_LEARNING_RATE);
	NominalMapping labelMapping = exampleSet.getAttributes().getLabel().getMapping();
	String classNeg = labelMapping.getNegativeString();
	String classPos = labelMapping.getPositiveString();
	double classValueNeg = labelMapping.getNegativeIndex();
	int numberOfAttributes = exampleSet.getAttributes().size();
	HyperplaneModel model = new HyperplaneModel(exampleSet, classNeg, classPos, kernel);
	model.init(new double[numberOfAttributes], 0);
	int rounds = getParameterAsInt(PARAMETER_ROUNDS);
	for (int round = 0; round <= rounds; round++) {
		double learnRate = getLearnRate(round, rounds, initLearnRate);
		Attributes attributes = exampleSet.getAttributes();
		for (Example example : exampleSet) {
			double prediction = model.predict(example);
			if (prediction != example.getLabel()) {
				double direction = (example.getLabel() == classValueNeg) ? -1 : 1;
				// adapting intercept
				model.setIntercept(model.getIntercept() + learnRate * direction);
				// adapting coefficients
				double coefficients[] = model.getCoefficients();
				int i = 0;
				for (Attribute attribute : attributes) {
					coefficients[i] += learnRate * direction * example.getValue(attribute);
					i++;
				}
			}
		}
	}
	return model;
}
開發者ID:rapidminer，項目名稱:rapidminer-studio，代碼行數:35，代碼來源:Perceptron.java

示例3: learn

import com.rapidminer.example.table.NominalMapping; //導入方法依賴的package包/類
public Model learn(ExampleSet exampleSet) throws OperatorException {
	Kernel kernel = getKernel();
	kernel.init(exampleSet);

	double initLearnRate = getParameterAsDouble(PARAMETER_LEARNING_RATE);
	NominalMapping labelMapping = exampleSet.getAttributes().getLabel().getMapping();
	String classNeg = labelMapping.getNegativeString();
	String classPos = labelMapping.getPositiveString();
	double classValueNeg = labelMapping.getNegativeIndex();
	int numberOfAttributes = exampleSet.getAttributes().size();
	HyperplaneModel model = new HyperplaneModel(exampleSet, classNeg, classPos, kernel);
	model.init(new double[numberOfAttributes], 0);
	for (int round = 0; round <= getParameterAsInt(PARAMETER_ROUNDS); round++) {
		double learnRate = getLearnRate(round, getParameterAsInt(PARAMETER_ROUNDS), initLearnRate);
		Attributes attributes = exampleSet.getAttributes();
		for (Example example: exampleSet) {
			double prediction = model.predict(example);
			if (prediction != example.getLabel()) {
				double direction = (example.getLabel() == classValueNeg)? -1 : 1;
				// adapting intercept
				model.setIntercept(model.getIntercept() + learnRate * direction);
				// adapting coefficients
				double coefficients[] = model.getCoefficients();
				int i = 0;
				for (Attribute attribute: attributes) {
					coefficients[i] += learnRate * direction * example.getValue(attribute);
					i++;
				}
			}
		}
	}
	return model;
}
開發者ID:rapidminer，項目名稱:rapidminer-5，代碼行數:34，代碼來源:Perceptron.java

示例4: doWork

import com.rapidminer.example.table.NominalMapping; //導入方法依賴的package包/類
@Override
public void doWork() throws OperatorException {
	// sanity checks
	ExampleSet exampleSet = exampleSetInput.getData(ExampleSet.class);

	// checking preconditions
	Attribute label = exampleSet.getAttributes().getLabel();
	if (label == null) {
		throw new UserError(this, 105);
	}
	if (!label.isNominal()) {
		throw new UserError(this, 101, label, "threshold finding");
	}
	exampleSet.recalculateAttributeStatistics(label);
	NominalMapping mapping = label.getMapping();
	if (mapping.size() != 2) {
		throw new UserError(this, 118, new Object[] { label, Integer.valueOf(mapping.getValues().size()),
				Integer.valueOf(2) });
	}
	if (exampleSet.getAttributes().getPredictedLabel() == null) {
		throw new UserError(this, 107);
	}
	boolean useExplictLabels = getParameterAsBoolean(PARAMETER_DEFINE_LABELS);

	double secondCost = getParameterAsDouble(PARAMETER_MISCLASSIFICATION_COSTS_SECOND);
	double firstCost = getParameterAsDouble(PARAMETER_MISCLASSIFICATION_COSTS_FIRST);
	if (useExplictLabels) {
		String firstLabel = getParameterAsString(PARAMETER_FIRST_LABEL);
		String secondLabel = getParameterAsString(PARAMETER_SECOND_LABEL);

		if (mapping.getIndex(firstLabel) == -1) {
			throw new UserError(this, 143, firstLabel, label.getName());
		}
		if (mapping.getIndex(secondLabel) == -1) {
			throw new UserError(this, 143, secondLabel, label.getName());
		}

		// if explicit order differs from order in data: internally swap costs.
		if (mapping.getIndex(firstLabel) > mapping.getIndex(secondLabel)) {
			double temp = firstCost;
			firstCost = secondCost;
			secondCost = temp;
		}
	}

	// check whether the confidence attributes are available
	if (exampleSet.getAttributes().getConfidence(mapping.getPositiveString()) == null) {
		throw new UserError(this, 113, Attributes.CONFIDENCE_NAME + "_" + mapping.getPositiveString());
	}
	if (exampleSet.getAttributes().getConfidence(mapping.getNegativeString()) == null) {
		throw new UserError(this, 113, Attributes.CONFIDENCE_NAME + "_" + mapping.getNegativeString());
	}
	// create ROC data
	ROCDataGenerator rocDataGenerator = new ROCDataGenerator(firstCost, secondCost);
	ROCData rocData = rocDataGenerator.createROCData(exampleSet, getParameterAsBoolean(PARAMETER_USE_EXAMPLE_WEIGHTS),
			ROCBias.getROCBiasParameter(this));

	// create plotter
	if (getParameterAsBoolean(PARAMETER_SHOW_ROC_PLOT)) {
		rocDataGenerator.createROCPlotDialog(rocData, true, true);
	}

	// create and return output
	exampleSetOutput.deliver(exampleSet);
	thresholdOutput.deliver(new Threshold(rocDataGenerator.getBestThreshold(), mapping.getNegativeString(), mapping
			.getPositiveString()));
}
開發者ID:transwarpio，項目名稱:rapidminer，代碼行數:68，代碼來源:ThresholdFinder.java

示例5: doWork

import com.rapidminer.example.table.NominalMapping; //導入方法依賴的package包/類
@Override
public void doWork() throws OperatorException {
	// sanity checks
	ExampleSet exampleSet = exampleSetInput.getData(ExampleSet.class);

	// checking preconditions
	Tools.hasNominalLabels(exampleSet, getOperatorClassName());
	Attribute label = exampleSet.getAttributes().getLabel();
	exampleSet.recalculateAttributeStatistics(label);
	NominalMapping mapping = label.getMapping();
	if (mapping.size() != 2) {
		throw new UserError(this, 118, label, Integer.valueOf(mapping.getValues().size()), Integer.valueOf(2));
	}
	if (exampleSet.getAttributes().getPredictedLabel() == null) {
		throw new UserError(this, 107);
	}
	boolean useExplictLabels = getParameterAsBoolean(PARAMETER_DEFINE_LABELS);

	double secondCost = getParameterAsDouble(PARAMETER_MISCLASSIFICATION_COSTS_SECOND);
	double firstCost = getParameterAsDouble(PARAMETER_MISCLASSIFICATION_COSTS_FIRST);
	if (useExplictLabels) {
		String firstLabel = getParameterAsString(PARAMETER_FIRST_LABEL);
		String secondLabel = getParameterAsString(PARAMETER_SECOND_LABEL);

		if (mapping.getIndex(firstLabel) == -1) {
			throw new UserError(this, 143, firstLabel, label.getName());
		}
		if (mapping.getIndex(secondLabel) == -1) {
			throw new UserError(this, 143, secondLabel, label.getName());
		}

		// if explicit order differs from order in data: internally swap costs.
		if (mapping.getIndex(firstLabel) > mapping.getIndex(secondLabel)) {
			double temp = firstCost;
			firstCost = secondCost;
			secondCost = temp;
		}
	}

	// check whether the confidence attributes are available
	if (exampleSet.getAttributes().getConfidence(mapping.getPositiveString()) == null) {
		throw new UserError(this, 113, Attributes.CONFIDENCE_NAME + "_" + mapping.getPositiveString());
	}
	if (exampleSet.getAttributes().getConfidence(mapping.getNegativeString()) == null) {
		throw new UserError(this, 113, Attributes.CONFIDENCE_NAME + "_" + mapping.getNegativeString());
	}
	// create ROC data
	ROCDataGenerator rocDataGenerator = new ROCDataGenerator(firstCost, secondCost);
	ROCData rocData = rocDataGenerator.createROCData(exampleSet, getParameterAsBoolean(PARAMETER_USE_EXAMPLE_WEIGHTS),
			ROCBias.getROCBiasParameter(this));

	// create plotter
	if (getParameterAsBoolean(PARAMETER_SHOW_ROC_PLOT)) {
		rocDataGenerator.createROCPlotDialog(rocData, true, true);
	}

	// create and return output
	exampleSetOutput.deliver(exampleSet);
	thresholdOutput.deliver(new Threshold(rocDataGenerator.getBestThreshold(), mapping.getNegativeString(), mapping
			.getPositiveString()));
}
開發者ID:rapidminer，項目名稱:rapidminer-studio，代碼行數:62，代碼來源:ThresholdFinder.java


注：本文中的com.rapidminer.example.table.NominalMapping.getPositiveString方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。