在windows 10上使用cnn keras进行花卉识别

在我与机器学习相关的项目中，使用CNN keras进行花卉识别。显示以下错误 错误：

关于守则：

#using Grid Search and Early stopping
es = EarlyStopping(monitor='val_acc', verbose=2, patience=25)
mc = ModelCheckpoint('./best_model_1.h5', monitor='val_acc', verbose=2, save_best_only=True)

Hyp_Model_1 = KerasClassifier(build_fn=Revised_1_fn)
#You need to pick the right hyper-parameters for your training (try with different ones)

learn_rate = [0.01]
batch_size = [32,75,100]
epochs = [5]

param_grid = dict(batch_size=batch_size, epochs=epochs, learn_rate = learn_rate)
randSearch_1 = GridSearchCV(estimator = Hyp_Model_1, param_grid=param_grid, cv=5)

new_grid_1 = randSearch_1.fit(X_train,y_train, validation_data = (X_val, y_val), verbose=2,callbacks=[es,mc])

---

正如错误消息中所暗示的，Keras不将

val_acc

识别为度量；您需要输入可用选项中列出的

val\u accurity

。

错误消息清楚地指导您了解确切的问题所在以及代码中需要更改的内容。

#using Grid Search and Early stopping
es = EarlyStopping(monitor='val_acc', verbose=2, patience=25)
mc = ModelCheckpoint('./best_model_1.h5', monitor='val_acc', verbose=2, save_best_only=True)

Hyp_Model_1 = KerasClassifier(build_fn=Revised_1_fn)
#You need to pick the right hyper-parameters for your training (try with different ones)

learn_rate = [0.01]
batch_size = [32,75,100]
epochs = [5]

param_grid = dict(batch_size=batch_size, epochs=epochs, learn_rate = learn_rate)
randSearch_1 = GridSearchCV(estimator = Hyp_Model_1, param_grid=param_grid, cv=5)

new_grid_1 = randSearch_1.fit(X_train,y_train, validation_data = (X_val, y_val), verbose=2,callbacks=[es,mc])