在Apache 3中计算PolynomialCurveFitter的R-平方

Question

Apache commons-math3 (version 3.6.1)类如OLSMultipleLinearRegression、SimpleRegression提供了计算RSquare (即calculateRSquared()、getRSquare() )的方法。但我无法找到任何这样的方法用于PolynomialCurveFitter？

现在我正像下面这样做。有什么普通的数学方法能做到这一点吗？

private PolynomialFunction getPolynomialFitter(List<List<Double>> pointlist) {
    final PolynomialCurveFitter fitter = PolynomialCurveFitter.create(2);
    final WeightedObservedPoints obs = new WeightedObservedPoints();
    for (List<Double> point : pointlist) {
        obs.add(point.get(0), point.get(1));
    }

    double[] fit = fitter.fit(obs.toList());
    System.out.printf("\nCoefficient %f, %f, %f", fit[0], fit[1], fit[2]);
    final PolynomialFunction fitted = new PolynomialFunction(fit);
    return fitted;
}
private double getRSquare(PolynomialFunction fitter, List<List<Double>> pointList) {
    final double[] coefficients = fitter.getCoefficients();
    double[] predictedValues = new double[pointList.size()];
    double residualSumOfSquares = 0;
    final DescriptiveStatistics descriptiveStatistics = new DescriptiveStatistics();
    for (int i=0; i< pointList.size(); i++) {
        predictedValues[i] = predict(coefficients, pointList.get(i).get(0));
        double actualVal = pointList.get(i).get(1);
        double t = Math.pow((predictedValues[i] - actualVal), 2);
        residualSumOfSquares  += t;
        descriptiveStatistics.addValue(actualVal);
    }
    final double avgActualValues = descriptiveStatistics.getMean();
    double totalSumOfSquares = 0;
    for (int i=0; i<pointList.size(); i++) {
        totalSumOfSquares += Math.pow( (predictedValues[i] - avgActualValues),2);
    }
    return 1.0 - (residualSumOfSquares/totalSumOfSquares);
}
final PolynomialFunction polynomial = getPolynomialFitter(trainData);
System.out.printf("\nPolynimailCurveFitter R-Square %f", getRSquare(polynomial, trainData));

Answer 1

这已经在apache-共用邮件列表中得到了回答。交叉张贴答案

OLSMultipleLinearRegression，SimpleRegression提供了一个返回calculateRSquared()、getRSquare()的方法。但我无法找到任何这样的方法用于PolynomialCurveFitter？ 现在我自己做，如下所示： 有什么普通的数学方法能做到这一点吗？

"PolynomialCurveFitter“是最小二乘优化器的语法糖/包装器之一。在(不可变)实例中不维护任何状态。

PolynomialFunction getPolynomialFitter(Listpointlist) { final PolynomialCurveFitter fitter = PolynomialCurveFitter.create(2)；final WeightedObservedPoints obs =新WeightedObservedPoints()；for (列表点: pointlist) { obs.add(point.get(0)，point.get(1))；} double[] fit = fitter.fit(obs.toList())；System.out.printf(“\n系数%f，%f，%f"，fit，fit1，fit2)；fit PolynomialFunction fit=新的PolynomialCurveFitter(Fit)；返回fit；}

这确实是预期的用例之一。

私有双getRSquare(PolynomialFunction fitter，List pointList) {最终double[]系数= fitter.getCoefficients()；double[] predictedValues =新doublepointList.size()；double residualSumOfSquares = 0；final descriptiveStatistics DescriptiveStatistics = new DescriptiveStatistics()；for (int i=0；i< pointList.size()；i++) {i++=预测(系数，PolynomialFunction(I)(0))；双en20#=#(I)(1)；double t=((-)，2)；en27# t；descriptiveStatistics.addValue(actualVal)；} final double avgActualValues = descriptiveStatistics.getMean()；double totalSumOfSquares = 0；for (int i=0；i

此处没有显示“预测”方法，但请注意，您在上面称为“适合者”的参数实际上是一个多项式函数：

http://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math4/analysis/polynomials/PolynomialFunction.html

因此：predictedValues[i] = fitter.value(pointList.get(i).get(0));

但除此之外，是的，来电者有责任选择他对模型质量的评估。

您可以直接使用类的最小二乘套件；然后“评估”对象将允许检索各种适合的度量：

http://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math4/fitting/leastsquares/LeastSquaresProblem.Evaluation.html

然而，他们可能仍然不是你想要的.