def run(self, max_iter=100):
candidates = self.generate_descendence(self.initialize_chromosomes(),
self.num_nc)
self.plotting(candidates)
best_candidate = candidates[0]
score = min(candidates[:, -1])
prev_score = np.Inf
for iteration in range(0, max_iter):
if prev_score > score:
candidates = self.generate_descendence(
self.initialize_chromosomes(), self.num_nc)
self.plotting(candidates)
prev_score = score
score = min(candidates[:, -1])
if prev_score > score:
best_candidate = candidates[0]
else:
print(
'Convergence at iteration {}.\nCandidate Chromosome: {}.\nScore: {}\nCenters at: {}'
.format(
iteration, best_candidate[0], best_candidate[2],
str(''.join(
['\n\t' + str(x) for x in best_candidate[1]]))))
self.plotting(best_candidate, single_cluster=True)
break
w, r = self.get_hyperparameters(best_candidate[0])
it_best = gk(self.data_scaled, 3, w, r)
points_closet_centroid = it_best.get_points_closet_centroid(
best_candidate[1])
pt.schema(points_closet_centroid, best_candidate[1],
points_closet_centroid[:, -1], best_candidate)
