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)
