def score_result(reducer_function, data, x_scaled, ini, dimensions, label_data, title): knn = Knn() score = [] valor_k = range(ini, dimensions) for k in valor_k: new_data = reducer_function(data, x_scaled, k) score.append(knn.avg(new_data, label_data)) Visualization.hit_rate_per_k(valor_k, score, title)
def run(self, alg, bean_list, filename="img.png", weighted=False): accuracy = [] #self.set_train_test_set(generator,bean_list) for k in self.k_values: for train in self.train_set: # Train alg.train([bean_list[a] for a in train]) for test in self.test_set: # Test result = alg.teste([bean_list[a] for a in test], k=k) # Result accuracy.append(Knn.accuracy(result)) print("acuracy knn {0} with k {1}".format(accuracy[-1], k)) self.mean_accuracy(accuracy) # Plot the graphic Visualization.hit_rate_per_k(self.mean_accuracy_list, self.k_values, filename, weighted)