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)