Method predict

ge/classify.py:10–19

(self, X, top_k_list)

class TopKRanker(OneVsRestClassifier):
    def predict(self, X, top_k_list):
        probs = numpy.asarray(super(TopKRanker, self).predict_proba(X))
        all_labels = []
        for i, k in enumerate(top_k_list):
            probs_ = probs[i, :]
            labels = self.classes_[probs_.argsort()[-k:]].tolist()
            probs_[:] = 0
            probs_[labels] = 1
            all_labels.append(probs_)
        return numpy.asarray(all_labels)


class Classifier(object):