Method auc

pattern/vector/__init__.py:1831–1844

Returns the area under the ROC-curve. Returns the probability (0.0-1.0) that a classifier will rank a random positive document (True) higher than a random negative one (False).

(self, documents=[], k=10)

        return ConfusionMatrix(self.classify, documents)

    def auc(self, documents=[], k=10):
        """ Returns the area under the ROC-curve.
            Returns the probability (0.0-1.0) that a classifier will rank 
            a random positive document (True) higher than a random negative one (False).
        """
        roc = [(0.0, 0.0), (1.0, 1.0)]
        for type, TP, TN, FP, FN in self.confusion_matrix(documents).split():
            x = FPR = float(FP) / ((FP + TN) or 1) # false positive rate
            y = TPR = float(TP) / ((TP + FN) or 1) #  true positive rate
            roc.append((x, y))
            #print "%s\t%s %s %s %s\t %s %s" % (TP, TN, FP, FN, FPR, TPR)
        roc = sorted(roc)
        # Trapzoidal rule: area = (a + b) * h / 2, where a=y0, b=y1 and h=x1-x0.
        return sum(0.5 * (x1 - x0) * (y1 + y0) for (x0, y0), (x1, y1) in sorted(izip(roc, roc[1:])))

    def save(self, path):
        self.test = None # Can't pickle instancemethods.