def init(self, n_pop, n_gen, w, c1, c2, data, dummiesList, createDummies, normalize, metric): print("#####################################") print("#OPTIMSATION PAR ESSAIM DE PARTICULE#") print("#####################################") print() x = queue.Queue() y = queue.Queue() z = queue.Queue() besties = queue.Queue() names = queue.Queue() iters = queue.Queue() if isinstance(self.listModels, str): if self.listModels == 'all': self.listModels = [ 'x', 'rrc', 'sgd', 'knn', 'svm', 'rbf', 'dtc', 'rdc', 'etc', 'gbc', 'abc', 'bac', 'lda', 'qda', 'gnb' ] else: self.listModels = ['x'] n = 4 mods = [self.listModels[i::n] for i in range(n)] threads = [] for part in mods: thread = threading.Thread(target=self.optimization, args=(part, n_pop, n_gen, w, c1, c2, data, dummiesList, createDummies, normalize, metric, x, y, besties, names, iters)) threads.append(thread) thread.start() for thread in threads: thread.join() return utility.res(heuristic="Optimisation par essaim de particules", x=list(x.queue), y=list(y.queue), z=list(z.queue), besties=list(besties.queue), names=list(names.queue), iters=list(iters.queue), metric=metric, path=self.path2, n_gen=n_gen - 1, self=self)
def init(self, n_gen, n_gen_vnd, kmax, n_neighbors, data, dummiesList, createDummies, normalize, metric): print("#################################") print("#RECHERCHE A VOISINNAGE VARIABLE#") print("#################################") print() x = queue.Queue() y = queue.Queue() z = queue.Queue() besties = queue.Queue() names = queue.Queue() iters = queue.Queue() if isinstance(self.listModels, str): if self.listModels == 'all': self.listModels = [ 'x', 'rrc', 'sgd', 'knn', 'svm', 'rbf', 'dtc', 'rdc', 'etc', 'gbc', 'abc', 'bac', 'lda', 'qda', 'gnb' ] else: self.listModels = ['x'] n = 4 mods = [self.listModels[i::n] for i in range(n)] threads = [] for part in mods: thread = threading.Thread(target=self.optimization, args=(part, n_gen, n_gen_vnd, kmax, n_neighbors, data, dummiesList, createDummies, normalize, metric, x, y, besties, names, iters)) threads.append(thread) thread.start() for thread in threads: thread.join() return utility.res(heuristic="Recherche à voisinage variable", x=list(x.queue), y=list(y.queue), z=list(z.queue), besties=list(besties.queue), names=list(names.queue), iters=list(iters.queue), metric=metric, path=self.path2, n_gen=n_gen - 1, self=self)
def init(self, n_pop, n_gen, cross_proba, F, data, dummiesList, createDummies, normalize, metric): print("#######################################") print("#ALGORITHME A EVOLUTION DIFFERENTIELLE#") print("#######################################") print() x = queue.Queue() y = queue.Queue() z = queue.Queue() besties = queue.Queue() names = queue.Queue() iters = queue.Queue() if isinstance(self.listModels, str): if self.listModels == 'all': self.listModels = [ 'x', 'rrc', 'sgd', 'knn', 'svm', 'rbf', 'dtc', 'rdc', 'etc', 'gbc', 'abc', 'bac', 'lda', 'qda', 'gnb' ] else: self.listModels = ['x'] n = 4 mods = [self.listModels[i::n] for i in range(n)] threads = [] for part in mods: thread = threading.Thread(target=self.natural_selection, args=(part, n_pop, n_gen, cross_proba, F, data, dummiesList, createDummies, normalize, metric, x, y, besties, names, iters)) threads.append(thread) thread.start() for thread in threads: thread.join() return utility.res(heuristic="Evolution différentielle", x=list(x.queue), y=list(y.queue), z=list(z.queue), besties=list(besties.queue), names=list(names.queue), iters=list(iters.queue), metric=metric, path=self.path2, n_gen=n_gen, self=self)
def init(self, temperature, alpha, final_temperature, data, dummiesList, createDummies, normalize, metric): print("###############") print("#RECUIT SIMULE#") print("###############") print() x = queue.Queue() y = queue.Queue() z = queue.Queue() besties = queue.Queue() names = queue.Queue() iters = queue.Queue() if isinstance(self.listModels, str): if self.listModels == 'all': self.listModels = [ 'x', 'rrc', 'sgd', 'knn', 'svm', 'rbf', 'dtc', 'rdc', 'etc', 'gbc', 'abc', 'bac', 'lda', 'qda', 'gnb' ] else: self.listModels = ['x'] n = 4 mods = [self.listModels[i::n] for i in range(n)] threads = [] for part in mods: thread = threading.Thread( target=self.optimization, args=(part, temperature, alpha, final_temperature, data, dummiesList, createDummies, normalize, metric, x, y, besties, names, iters)) threads.append(thread) thread.start() for thread in threads: thread.join() return utility.res(heuristic="Recuit simulé", x=list(x.queue), y=list(y.queue), z=list(z.queue), besties=list(besties.queue), names=list(names.queue), iters=list(iters.queue), metric=metric, path=self.path2, n_gen=temperature - 1, self=self)