将我的数据集拟合到我的模型中时出现问题 python

Question

我在将数据集拟合到模型中时遇到问题。我不知道这个错误代表什么，当然也不知道如何修复它。谢谢！

import numpy as np
import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler
from keras.models import Sequential
from keras.layers import Dense


dataset = pd.read_csv('Churn_Modelling.csv')
dataset

X=dataset.iloc[:,3:13].values
Y=dataset.iloc[:,13].values

from sklearn.preprocessing import LabelEncoder, OneHotEncoder
lableencoder_X_2 = LabelEncoder()
X[:, 2] = lableencoder_X_2.fit_transform(X[:, 2])

ct = ColumnTransformer([('ohe', OneHotEncoder(), [1])], remainder='passthrough')
X = np.array(ct.fit_transform(X), dtype = str)
X = X[:, 1:]

classifier.add(Dense(units = 6,kernel_initializer = 'uniform',activation ='relu',input_dim = 11))

classifier.add(Dense(units = 6,kernel_initializer = 'uniform',activation ='relu'))

classifier.add(Dense(units= 1, kernel_initializer = 'uniform',activation = 'sigmoid'))

classifier.compile(optimizer = 'adam', loss = 'binary_crssentropy', metrics = ['accuracy'])

# fit our dataset to our module.
classifier.fit(X_train, y_train, batch_size = 10, epochs = 100)

错误：

Answer 1

嗯，错误信息很清楚。损失函数应该是 binary_crossentropy 而不是 binary_crssentropy

将我的数据集拟合到我的模型中时出现问题 python

problem fiting my dataset into my model python

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