containsKernel = true; KernelEstimator ke = (KernelEstimator) m_Distribution[j]; int numK = ke.getNumKernels(); String temps = "K" + numK + ": mean (weight)"; if (maxAttWidth < temps.length()) { if (ke.getNumKernels() > 0) { double[] means = ke.getMeans(); double[] weights = ke.getWeights(); for (int k = 0; k < ke.getNumKernels(); k++) { String m = Utils.doubleToString(means[k], maxWidth, 4).trim(); m += " (" for (int k = 0; k < m_Instances.numClasses(); k++) { KernelEstimator ke = (KernelEstimator) m_Distributions[counter][k]; String nk = "" + ke.getNumKernels(); temp.append(pad(nk, " ", maxWidth + 1 - nk.length(), true)); for (int k = 0; k < m_Instances.numClasses(); k++) { KernelEstimator ke = (KernelEstimator) m_Distributions[counter][k]; if (ke.getNumKernels() > maxK) { maxK = ke.getNumKernels(); double[] weights = ke.getWeights(); String m = "--"; if (ke.getNumKernels() == 0) { m = "" + 0; } else if (j < ke.getNumKernels()) { m = Utils.doubleToString(means[j], maxWidth, 4).trim();
containsKernel = true; KernelEstimator ke = (KernelEstimator) m_Distribution[j]; int numK = ke.getNumKernels(); String temps = "K" + numK + ": mean (weight)"; if (maxAttWidth < temps.length()) { if (ke.getNumKernels() > 0) { double[] means = ke.getMeans(); double[] weights = ke.getWeights(); for (int k = 0; k < ke.getNumKernels(); k++) { String m = Utils.doubleToString(means[k], maxWidth, 4).trim(); m += " (" for (int k = 0; k < m_Instances.numClasses(); k++) { KernelEstimator ke = (KernelEstimator) m_Distributions[counter][k]; String nk = "" + ke.getNumKernels(); temp.append(pad(nk, " ", maxWidth + 1 - nk.length(), true)); for (int k = 0; k < m_Instances.numClasses(); k++) { KernelEstimator ke = (KernelEstimator) m_Distributions[counter][k]; if (ke.getNumKernels() > maxK) { maxK = ke.getNumKernels(); double[] weights = ke.getWeights(); String m = "--"; if (ke.getNumKernels() == 0) { m = "" + 0; } else if (j < ke.getNumKernels()) { m = Utils.doubleToString(means[j], maxWidth, 4).trim();