YAO/YAO-optimizer
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Newnius
2020-05-02 16:24:53 +08:00
parent 37b670e338
commit 5a71f23db5
2 changed files with 8 additions and 6 deletions
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train.py
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@@ -69,8 +69,8 @@ def fit_lstm(train, batch_size2, nb_epoch, neurons):
model.compile(loss='mean_squared_error', optimizer='adam')
for i in range(nb_epoch):
model.fit(X, y, epochs=1, batch_size=batch_size2, verbose=0, shuffle=False)
#loss = model.evaluate(X, y)
#print("Epoch {}/{}, loss = {}".format(i, nb_epoch, loss))
# loss = model.evaluate(X, y)
# print("Epoch {}/{}, loss = {}".format(i, nb_epoch, loss))
model.reset_states()
return model
@@ -95,6 +95,8 @@ def experiment(repeats, series, seed):
batch_size = 32
if supervised_values.shape[0] < 100:
batch_size = 16
if supervised_values.shape[0] < 60:
batch_size = 8
test_data_num = batch_size
# split data into train and test-sets
@@ -150,9 +152,9 @@ results = DataFrame()
with_seed = experiment(repeats, series, True)
results['with-seed'] = with_seed
# without seeding
without_seed = experiment(repeats, series, False)
results['without-seed'] = without_seed
# without_seed = experiment(repeats, series, False)
# results['without-seed'] = without_seed
# summarize results
print(results.describe())
# save boxplot
results.boxplot()
# results.boxplot()