回答編集履歴
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修正したコードを追記
test
CHANGED
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@@ -43,3 +43,141 @@
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```
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は不要ですね。
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---
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**【追記】**
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実際に実行したコード
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```Python
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import numpy as np
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import matplotlib.pyplot as plt
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from keras.datasets import mnist
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from keras.layers import Activation, Dense, Dropout
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from keras.models import Sequential, load_model
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from keras.utils.np_utils import to_categorical
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from keras import optimizers
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from keras import models
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from keras import layers
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%matplotlib inline
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(X_train, y_train), (X_test, y_test) = mnist.load_data()
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X_train = X_train.reshape(X_train.shape[0], 784)[:6000]
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X_test = X_test.reshape(X_test.shape[0], 784)[:1000]
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y_train = to_categorical(y_train)[:6000]
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y_test = to_categorical(y_test)[:1000]
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model = Sequential()
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model.add(Dense(256, input_dim=784))
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model.add(Activation("sigmoid"))
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model.add(Dense(128))
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model.add(Activation("sigmoid"))
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model.add(Dropout(rate=0.5))
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model.add(Dense(10))
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model.add(Activation("softmax"))
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sgd = optimizers.SGD(lr=0.1)
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model.compile(optimizer=sgd, loss="categorical_crossentropy", metrics=["accuracy"])
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model.summary()
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history = model.fit(
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X_train,
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y_train,
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batch_size=32,
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epochs=5,
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verbose=1,
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validation_data=(X_test, y_test),
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)
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acc = history.history["acc"]
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val_acc = history.history["val_acc"]
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loss = history.history["loss"]
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val_loss = history.history["val_loss"]
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epochs = range(1, len(acc)+1)
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plt.plot(epochs, acc, label="acc", ls="-", marker="o")
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plt.plot(epochs, val_acc, label="val_acc", ls="-", marker="x")
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plt.ylabel("accuracy")
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plt.xlabel("epoch")
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plt.legend(loc="best")
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```
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実行した結果（途中経過は省略しております）
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です。
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もしこれで表示できないのであれば、``matplotlib`` のインストール等に失敗している可能性があります。
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試しに最小限のコード
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```Python
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%matplotlib inline
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import matplotlib.pyplot as plt
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plt.plot([0,1],[0,1])
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```
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にてグラフが描画できるか確認してみてください。
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