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23-05-24 | 2

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pyplot 을 추가하여 loss 와 acc 가 학습할때 어떻게 변화하는지 적용
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jung-geun
2023-05-24 15:39:17 +09:00
parent 27d40ab56c
commit 7a612e4ca7
4 changed files with 433 additions and 131 deletions
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mnist.py
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@@ -77,7 +77,7 @@ def auto_tuning(n_particles=n_particles, maxiter=maxiter, c0=c0, c1=c1, w=w):
optimizer = keras.optimizers.SGD(lr=lr, momentum=momentun, decay=decay, nesterov=nestrov)
pso_m = PSO(model=model, loss_method=loss, n_particles=n_particles, x_train=x_train, y_train=y_train)
pso_m = PSO(model=model, loss_method=loss, n_particles=n_particles)
# c0 : 지역 최적값 중요도
# c1 : 전역 최적값 중요도
# w : 관성 (현재 속도를 유지하는 정도)
@@ -128,7 +128,7 @@ def get_score(model):
# plt.imshow(x_test[not_correct[i]].reshape(28,28), cmap='Greys')
# plt.show()
get_score(auto_tuning(n_particles=30, maxiter=1000, c0=0.5, c1=1.5, w=0.75))
get_score(auto_tuning(n_particles=30, maxiter=50, c0=0.5, c1=1.5, w=0.75))
# %%