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)
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)
