keras - 我的数据集由（12 个输入，13 个输出）13 个属性组成，我想计算数据集每一行的指标，但显示错误

Question

from numpy import loadtxt from keras.models import Sequential from keras.layers import Dense from matplotlib import pyplot

from sklearn.preprocessing import MinMaxScaler
# load the dataset
dataset = loadtxt('train.csv', delimiter=',')
scaler = MinMaxScaler(feature_range=(0, 1))
scaler.fit(dataset)
normalized = scaler.transform(dataset)

for row in normalized:

# split into input (X) and output (y) variables
    X = row[0:13]
    y = row[13] 
# define the keras model
    model = Sequential()
    model.add(Dense(12, input_dim=13, activation='relu'))
    model.add(Dense(16, activation='relu'))
    model.add(Dense(20, activation='relu'))
    model.add(Dense(16, activation='relu'))
    model.add(Dense(1, activation='relu'))
# compile the keras model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['mse', 'mae', 'mape'])

history =model.fit(X, y, epochs=20,batch_size=1 , verbose=2)

pyplot.plot(history.history['mse'])
pyplot.plot(history.history['mae'])
pyplot.plot(history.history['mape'])
pyplot.show() 

标签： kerastf.keras

Answer 1

根据错误消息，输入X inmodel.fit的形状不正确。模型期望输入是形状为(13,)的数组，但模型的输入是(1,)形状的数组。打印 X 和 y 值并验证它们是否X = [[1,2,3,4,...13]] and Y = [[0]]像这样存储为列表列表。X[0] and y[0]在这种情况下，让步model.fit方法。