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Java SignificanceTestResult类代码示例

本文整理汇总了Java中com.rapidminer.tools.math.SignificanceTestResult类的典型用法代码示例。如果您正苦于以下问题：Java SignificanceTestResult类的具体用法？Java SignificanceTestResult怎么用？Java SignificanceTestResult使用的例子？那么, 这里精选的类代码示例或许可以为您提供帮助。


SignificanceTestResult类属于com.rapidminer.tools.math包，在下文中一共展示了SignificanceTestResult类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。

示例1: doWork

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
/** Writes the attribute set to a file. */
@Override
public void doWork() throws OperatorException {
	List<PerformanceVector> allVectors = performanceExtender.getData(PerformanceVector.class);

	if (allVectors.size() < getMinSize()) {
		throw new UserError(this, 123, PerformanceVector.class, getMinSize() + "");
	}

	if (allVectors.size() > getMaxSize()) {
		throw new UserError(this, 124, PerformanceVector.class, getMaxSize() + "");
	}

	PerformanceVector[] allVectorsArray = new PerformanceVector[allVectors.size()];
	allVectors.toArray(allVectorsArray);
	// // create result array
	// IOObject[] resultArray = new IOObject[allVectors.size() + 1];
	// System.arraycopy(allVectorsArray, 0, resultArray, 0, allVectorsArray.length);

	SignificanceTestResult result = performSignificanceTest(allVectorsArray, getParameterAsDouble(PARAMETER_ALPHA));

	performanceExtender.passDataThrough();
	significanceOutput.deliver(result);
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:25，代码来源:SignificanceTestOperator.java

示例2: performSignificanceTest

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
@Override
public SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha)
		throws OperatorException {
	AnovaCalculator calculator = new AnovaCalculator();
	calculator.setAlpha(alpha);

	for (int i = 0; i < allVectors.length; i++) {
		PerformanceCriterion pc = allVectors[i].getMainCriterion();
		calculator.addGroup(pc.getAverageCount(), pc.getAverage(), pc.getVariance());
	}

	try {
		SignificanceTestResult testResult = calculator.performSignificanceTest();
		this.probability = testResult.getProbability();
		return testResult;
	} catch (SignificanceCalculationException e) {
		throw new UserError(this, 920, e.getMessage());
	}
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:20，代码来源:AnovaSignificanceTestOperator.java

示例3: doWork

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
/** Writes the attribute set to a file. */
	@Override
	public void doWork() throws OperatorException {
		List<PerformanceVector> allVectors = performanceExtender.getData(PerformanceVector.class);
		
		if (allVectors.size() < getMinSize()) {
			throw new UserError(this, 123, PerformanceVector.class, getMinSize() + "");
		}

		if (allVectors.size() > getMaxSize()) {
			throw new UserError(this, 124, PerformanceVector.class, getMaxSize() + "");
		}
		
		PerformanceVector[] allVectorsArray = new PerformanceVector[allVectors.size()];
		allVectors.toArray(allVectorsArray);
//		// create result array
//		IOObject[] resultArray = new IOObject[allVectors.size() + 1];
//		System.arraycopy(allVectorsArray, 0, resultArray, 0, allVectorsArray.length);
		
		SignificanceTestResult result = performSignificanceTest(allVectorsArray, getParameterAsDouble(PARAMETER_ALPHA));
		
		performanceExtender.passDataThrough();
		significanceOutput.deliver(result);
	}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:25，代码来源:SignificanceTestOperator.java

示例4: performSignificanceTest

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
@Override
public SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha) throws OperatorException {
	AnovaCalculator calculator = new AnovaCalculator();
	calculator.setAlpha(alpha);

	for (int i = 0; i < allVectors.length; i++) {
		PerformanceCriterion pc = allVectors[i].getMainCriterion();
		calculator.addGroup(pc.getAverageCount(), pc.getAverage(), pc.getVariance());
	}

	try {
		SignificanceTestResult testResult = calculator.performSignificanceTest();
		this.probability = testResult.getProbability();
		return testResult;
	} catch (SignificanceCalculationException e) {
		throw new UserError(this, 920, e.getMessage());
	}
}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:19，代码来源:AnovaSignificanceTestOperator.java

示例5: performSignificanceTest

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
@Override
public SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha) {
	double[][] resultMatrix = new double[allVectors.length][allVectors.length];
	for (int i = 0; i < allVectors.length; i++) {
		for (int j = 0; j < i + 1; j++) {
			resultMatrix[i][j] = Double.NaN; // fill lower triangle with
		}
		// NaN --> empty in result
		// string
		for (int j = i + 1; j < allVectors.length; j++) {
			resultMatrix[i][j] = getProbability(allVectors[i].getMainCriterion(), allVectors[j].getMainCriterion());
		}
	}
	return new TTestSignificanceTestResult(allVectors, resultMatrix, alpha);
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:16，代码来源:TTestSignificanceTestOperator.java

示例6: GroupedANOVAOperator

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
public GroupedANOVAOperator(OperatorDescription desc) {
	super(desc);
	getTransformer().addRule(new GenerateNewMDRule(significanceOutput, SignificanceTestResult.class));
	getTransformer().addPassThroughRule(exampleSetInput, exampleSetOutput);
	exampleSetInput.addPrecondition(new AttributeSetPrecondition(exampleSetInput, AttributeSetPrecondition
			.getAttributesByParameter(this, PARAMETER_ANOVA_ATTRIBUTE), Ontology.NUMERICAL));
	exampleSetInput.addPrecondition(new AttributeSetPrecondition(exampleSetInput, AttributeSetPrecondition
			.getAttributesByParameter(this, PARAMETER_GROUP_BY_ATTRIBUTE), Ontology.NOMINAL));
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:10，代码来源:GroupedANOVAOperator.java

示例7: performSignificanceTest

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
@Override
public SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha) {
	double[][] resultMatrix = new double[allVectors.length][allVectors.length];
	for (int i = 0; i < allVectors.length; i++) {
		for (int j = 0; j < (i + 1); j++)
			resultMatrix[i][j] = Double.NaN; // fill lower triangle with
		// NaN --> empty in result
		// string
		for (int j = i + 1; j < allVectors.length; j++) {
			resultMatrix[i][j] = getProbability(allVectors[i].getMainCriterion(), allVectors[j].getMainCriterion());
		}
	}
	return new TTestSignificanceTestResult(allVectors, resultMatrix, alpha);
}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:15，代码来源:TTestSignificanceTestOperator.java

示例8: GroupedANOVAOperator

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
public GroupedANOVAOperator(OperatorDescription desc) {
	super(desc);
	getTransformer().addRule(new GenerateNewMDRule(significanceOutput, SignificanceTestResult.class));
	getTransformer().addPassThroughRule(exampleSetInput, exampleSetOutput);
	exampleSetInput.addPrecondition(new AttributeSetPrecondition(exampleSetInput, AttributeSetPrecondition.getAttributesByParameter(this, PARAMETER_ANOVA_ATTRIBUTE), Ontology.NUMERICAL));
	exampleSetInput.addPrecondition(new AttributeSetPrecondition(exampleSetInput, AttributeSetPrecondition.getAttributesByParameter(this, PARAMETER_GROUP_BY_ATTRIBUTE), Ontology.NOMINAL));
}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:8，代码来源:GroupedANOVAOperator.java

示例9: calculateANOVA

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
private void calculateANOVA() throws SignificanceCalculationException {
	double alpha = -1;
	String alphaString = alphaField.getText();
	try {
		alpha = Double.parseDouble(alphaString);
	} catch (NumberFormatException e) {
		SwingTools.showVerySimpleErrorMessage("sign_lvl_between_0_1");
	}

	if ((alpha < 0) || (alpha > 1)) {
		SwingTools.showVerySimpleErrorMessage("sign_lvl_between_0_1");			
	} else {
		this.calculator.clearGroups();
		this.calculator.setAlpha(alpha);
		for (int i = 0; i < tableModel.getRowCount(); i++) {
			double mean = ((Double) tableModel.getValueAt(i, 0)).doubleValue();
			double variance = ((Double) tableModel.getValueAt(i, 1)).doubleValue();
			int number = ((Integer) tableModel.getValueAt(i, 2)).intValue();
			calculator.addGroup(number, mean, variance);
		}
		if (tableModel.getRowCount() < 2) {
			SwingTools.showVerySimpleErrorMessage("two_rows_to_calc_anova_test");
			return;
		}

		SignificanceTestResult result = calculator.performSignificanceTest();
		SwingTools.showResultsDialog("anova", ResultDisplayTools.createVisualizationComponent(result, null, "ANOVA Result"));
	}
}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:30，代码来源:AnovaCalculatorDialog.java

示例10: SignificanceTestOperator

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
public SignificanceTestOperator(OperatorDescription description) {
	super(description);
	performanceExtender.start();
	getTransformer().addRule(new GenerateNewMDRule(significanceOutput, SignificanceTestResult.class));
	getTransformer().addRule(performanceExtender.makePassThroughRule());
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:7，代码来源:SignificanceTestOperator.java

示例11: doWork

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
@Override
public void doWork() throws OperatorException {
	ExampleSet inputSet = exampleSetInput.getData(ExampleSet.class);
	ExampleSet exampleSet = new NonSpecialAttributesExampleSet(inputSet);

	// determine anova and grouping attributes
	List<String> nominalAttributes = new ArrayList<String>();
	List<String> numericalAttributes = new ArrayList<String>();
	Iterator<Attribute> a = exampleSet.getAttributes().allAttributes();
	while (a.hasNext()) {
		Attribute attribute = a.next();
		if (attribute.isNominal()) {
			nominalAttributes.add(attribute.getName());
		} else if (attribute.isNumerical()) {
			numericalAttributes.add(attribute.getName());
		}
	}

	// init "inner" operator
	GroupedANOVAOperator groupedAnovaOperator = null;
	try {
		groupedAnovaOperator = OperatorService.createOperator(GroupedANOVAOperator.class);
	} catch (OperatorCreationException e) {
		throw new UserError(this, 109, GroupedANOVAOperator.class.getName());
	}
	double significanceLevel = getParameterAsDouble(GroupedANOVAOperator.PARAMETER_SIGNIFICANCE_LEVEL);
	groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_SIGNIFICANCE_LEVEL, significanceLevel + "");
	groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_ONLY_DISTINCT,
			getParameterAsBoolean(GroupedANOVAOperator.PARAMETER_ONLY_DISTINCT) + "");

	// calculate all values
	double[][] probabilities = new double[numericalAttributes.size()][nominalAttributes.size()];
	for (int numericalCounter = 0; numericalCounter < probabilities.length; numericalCounter++) {
		String numericalAttributeName = numericalAttributes.get(numericalCounter);
		for (int nominalCounter = 0; nominalCounter < probabilities[numericalCounter].length; nominalCounter++) {
			String nominalAttributeName = nominalAttributes.get(nominalCounter);
			groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_ANOVA_ATTRIBUTE, numericalAttributeName);
			groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_GROUP_BY_ATTRIBUTE, nominalAttributeName);
			SignificanceTestResult testResult = groupedAnovaOperator.apply((ExampleSet) exampleSet.clone());
			probabilities[numericalCounter][nominalCounter] = testResult.getProbability();
		}
	}

	// create and return result
	exampleSetOutput.deliver(exampleSet);
	anovaOutput.deliver(new ANOVAMatrix(probabilities, numericalAttributes, nominalAttributes, significanceLevel));
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:48，代码来源:ANOVAMatrixOperator.java

示例12: apply

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
public SignificanceTestResult apply(ExampleSet exampleSet) throws OperatorException {
	// init and checks
	String attributeName = getParameterAsString(PARAMETER_ANOVA_ATTRIBUTE);
	String groupByAttributeName = getParameterAsString(PARAMETER_GROUP_BY_ATTRIBUTE);
	boolean onlyDistinct = getParameterAsBoolean(PARAMETER_ONLY_DISTINCT);

	Attribute anovaAttribute = exampleSet.getAttributes().get(attributeName);
	if (anovaAttribute == null) {
		throw new AttributeNotFoundError(this, PARAMETER_ANOVA_ATTRIBUTE,
				getParameterAsString(PARAMETER_ANOVA_ATTRIBUTE));
	}
	if (anovaAttribute.isNominal()) {
		throw new UserError(this, 104, new Object[] { "anova calculation",
				this.getParameterAsString(PARAMETER_ANOVA_ATTRIBUTE) });
	}

	Attribute groupByAttribute = exampleSet.getAttributes().get(groupByAttributeName);
	if (groupByAttribute == null) {
		throw new AttributeNotFoundError(this, PARAMETER_GROUP_BY_ATTRIBUTE,
				getParameterAsString(PARAMETER_GROUP_BY_ATTRIBUTE));
	}
	if (!groupByAttribute.isNominal()) {
		throw new UserError(this, 103, new Object[] { "the parameter grouping by",
				this.getParameterAsString(PARAMETER_GROUP_BY_ATTRIBUTE) });
	}

	// create anova calculator
	AnovaCalculator anovaCalculator = new AnovaCalculator();
	double alpha = getParameterAsDouble(PARAMETER_SIGNIFICANCE_LEVEL);
	anovaCalculator.setAlpha(alpha);

	// add groups
	SplittedExampleSet grouped = SplittedExampleSet.splitByAttribute(exampleSet, groupByAttribute);
	AggregationFunction meanFunction = new AverageFunction();
	AggregationFunction varianceFunction = new VarianceFunction();
	for (int i = 0; i < grouped.getNumberOfSubsets(); i++) {
		grouped.selectSingleSubset(i);
		double[] values = getValues(grouped, anovaAttribute, onlyDistinct);
		double mean = meanFunction.calculate(values);
		double variance = varianceFunction.calculate(values);
		anovaCalculator.addGroup(grouped.size(), mean, variance);
	}

	// calculate and return result
	SignificanceTestResult result = null;
	try {
		result = anovaCalculator.performSignificanceTest();
	} catch (SignificanceCalculationException e) {
		throw new UserError(this, 920, e.getMessage());
	}

	exampleSetOutput.deliver(exampleSet);

	return result;
}
开发者ID:transwarpio，项目名称:rapidminer，代码行数:56，代码来源:GroupedANOVAOperator.java

示例13: doWork

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
@Override
public void doWork() throws OperatorException {
	ExampleSet inputSet = exampleSetInput.getData(ExampleSet.class);
	ExampleSet exampleSet = new NonSpecialAttributesExampleSet(inputSet);

	// determine anova and grouping attributes
	List<String> nominalAttributes = new ArrayList<String>();
	List<String> numericalAttributes = new ArrayList<String>();
	Iterator<Attribute> a = exampleSet.getAttributes().allAttributes();
	while (a.hasNext()) {
		Attribute attribute = a.next();
		if (attribute.isNominal())
			nominalAttributes.add(attribute.getName());
		else if (attribute.isNumerical())
			numericalAttributes.add(attribute.getName());
	}

	// init "inner" operator
	GroupedANOVAOperator groupedAnovaOperator = null;
	try {
		groupedAnovaOperator = OperatorService.createOperator(GroupedANOVAOperator.class);
	} catch (OperatorCreationException e) {
		throw new UserError(this, 109, GroupedANOVAOperator.class.getName());
	}
	double significanceLevel = getParameterAsDouble(GroupedANOVAOperator.PARAMETER_SIGNIFICANCE_LEVEL);
	groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_SIGNIFICANCE_LEVEL, significanceLevel + "");
	groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_ONLY_DISTINCT, getParameterAsBoolean(GroupedANOVAOperator.PARAMETER_ONLY_DISTINCT) + "");

	// calculate all values
	double[][] probabilities = new double[numericalAttributes.size()][nominalAttributes.size()];
	for (int numericalCounter = 0; numericalCounter < probabilities.length; numericalCounter++) {
		String numericalAttributeName = numericalAttributes.get(numericalCounter);
		for (int nominalCounter = 0; nominalCounter < probabilities[numericalCounter].length; nominalCounter++) {
			String nominalAttributeName = nominalAttributes.get(nominalCounter);
			groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_ANOVA_ATTRIBUTE, numericalAttributeName);
			groupedAnovaOperator.setParameter(GroupedANOVAOperator.PARAMETER_GROUP_BY_ATTRIBUTE, nominalAttributeName);
			SignificanceTestResult testResult = groupedAnovaOperator.apply((ExampleSet)exampleSet.clone());
			probabilities[numericalCounter][nominalCounter] = testResult.getProbability();
		}			
	}

	// create and return result
	exampleSetOutput.deliver(exampleSet);
	anovaOutput.deliver(new ANOVAMatrix(probabilities, numericalAttributes, nominalAttributes, significanceLevel));		
}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:46，代码来源:ANOVAMatrixOperator.java

示例14: apply

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
public SignificanceTestResult apply(ExampleSet exampleSet) throws OperatorException {
	// init and checks
	String attributeName = getParameterAsString(PARAMETER_ANOVA_ATTRIBUTE);
	String groupByAttributeName = getParameterAsString(PARAMETER_GROUP_BY_ATTRIBUTE);
	boolean onlyDistinct = getParameterAsBoolean(PARAMETER_ONLY_DISTINCT);

	Attribute anovaAttribute = exampleSet.getAttributes().get(attributeName);
	if (anovaAttribute == null) {
		throw new UserError(this, 111, this.getParameterAsString(PARAMETER_ANOVA_ATTRIBUTE));
	}
	if (anovaAttribute.isNominal()) {
		throw new UserError(this, 104, new Object[] { "anova calculation", this.getParameterAsString(PARAMETER_ANOVA_ATTRIBUTE)});
	}

	Attribute groupByAttribute = exampleSet.getAttributes().get(groupByAttributeName);
	if (groupByAttribute == null) {
		throw new UserError(this, 111, this.getParameterAsString(PARAMETER_GROUP_BY_ATTRIBUTE));
	}
	if (!groupByAttribute.isNominal()) {
		throw new UserError(this, 103, new Object[] {"the parameter grouping by", this.getParameterAsString(PARAMETER_GROUP_BY_ATTRIBUTE)});
	}

	// create anova calculator
	AnovaCalculator anovaCalculator = new AnovaCalculator();
	double alpha = getParameterAsDouble(PARAMETER_SIGNIFICANCE_LEVEL);
	anovaCalculator.setAlpha(alpha);

	// add groups
	SplittedExampleSet grouped = SplittedExampleSet.splitByAttribute(exampleSet, groupByAttribute);
	AggregationFunction meanFunction = new AverageFunction();
	AggregationFunction varianceFunction = new VarianceFunction();
	for (int i = 0; i < grouped.getNumberOfSubsets(); i++) {
		grouped.selectSingleSubset(i);
		double[] values = getValues(grouped, anovaAttribute, onlyDistinct);
		double mean = meanFunction.calculate(values);
		double variance = varianceFunction.calculate(values);
		anovaCalculator.addGroup(grouped.size(), mean, variance);
	}

	// calculate and return result
	SignificanceTestResult result = null;
	try {
		result = anovaCalculator.performSignificanceTest();
	} catch (SignificanceCalculationException e) {
		throw new UserError(this, 920, e.getMessage());
	}

	exampleSetOutput.deliver(exampleSet);

	return result;
}
开发者ID:rapidminer，项目名称:rapidminer-5，代码行数:52，代码来源:GroupedANOVAOperator.java

示例15: performSignificanceTest

import com.rapidminer.tools.math.SignificanceTestResult; //导入依赖的package包/类
/**
 * Returns the result of the significance test for the given performance vector collection.
 */
public abstract SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha)
		throws OperatorException;
开发者ID:transwarpio，项目名称:rapidminer，代码行数:6，代码来源:SignificanceTestOperator.java


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