def cforange_best_natts(input_dict): import orange import orngFSS data = input_dict['dataset'] scores = input_dict['scores'] n = int(input_dict['n']) new_dataset = orngFSS.selectBestNAtts(data,scores,n) output_dict={} output_dict['new_dataset'] = new_dataset return output_dict
def __call__(self, data, weight=None): ma = orngFSS.attMeasure(data) filtered = orngFSS.selectBestNAtts(data, ma, self.N) model = orange.BayesLearner(filtered) return BayesFSS_Classifier(classifier=model, N=self.N, name=self.name)