Question

我正在测试和训练文本数据集，但出现此错误。 CSV文件包含文本。

运行代码时，它会提供输出：

constructor(private fb: FormBuilder) { this.form = fb.group({ name: fb.control('foo bar', Validators.required), address: fb.group({ city: ['box',Validators.required], town: ['qux',Validators.required], }) }); }

这里ValueError: could not convert string to float: b'user1'是数据集中的文本

代码：

user1

完整的追溯错误：

from keras.models import Sequential
from keras.layers.core import Dense
from sklearn.model_selection import train_test_split
import numpy as np


seed = 9
np.random.seed(seed)

dataset = np.loadtxt('E:/7th Semester/FYP/ini/New 
folder/MBAT/DataSet/train_data.csv', delimiter=',', skiprows=1)


X = dataset[:,0:8]
Y = dataset[:,8]

(X_train, X_test, Y_train, Y_test) = train_test_split(X, Y, test_size=0.33, 
random_state=seed)


model = Sequential()
model.add(Dense(8, input_dim=8, init='uniform', activation='relu'))
model.add(Dense(6, init='uniform', activation='relu'))
model.add(Dense(1, init='uniform', activation='sigmoid'))


model.compile(loss='binary_crossentropy', optimizer='adam', metrics= 
['accuracy'])
model.fit(X_train, Y_train, validation_data=(X_test, Y_test), nb_epoch=100, 
batch_size=5)

scores = model.evaluate(X_test, Y_test)
print ("Accuracy: %.2f%%" %(scores[1]*100))

Answer 1

根据numpy的官方文档，从func getWg() *sync.WaitGroup { return &sync.WaitGroup{} } getWg().Wait() // Works, you can call methods on the return value m := map[int]*sync.WaitGroup{ 1: &sync.WaitGroup{}, } m[1].Wait() // Also works得到的数组的dtype为numpy.loadtxt()。现在，float是一个字符串，无法转换为user1，因此，您将收到此错误。您可以尝试以下操作：

float

ValueError：无法将字符串转换为浮点型：b'user1'

1 个答案: