在 python 中添加输出层的困难

Question

当我尝试运行代码时收到此错误：

File "C:Usersolakuanaconda3libsite-packageskeraslegacyinterfaces.py", line 91, in wrapper
return func(*args, **kwargs)
TypeError: __init__() missing 1 required positional argument: 'units'".

我的代码：

# Importing the relevant libraries.
import numpy as np
import pandas as pd

#importing the dataset
dataset = pd.read_csv ('Churn_Modelling.csv')
X = dataset.iloc[:, 3:13].values
y = dataset.iloc[:, 13].values
# Encoding categorical data
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_X_1 = LabelEncoder()
X[:, 1] = labelencoder_X_1.fit_transform(X[:, 1])
labelencoder_X_2 = LabelEncoder()
X[:, 2] = labelencoder_X_2.fit_transform(X[:, 2])
onehotencoder = OneHotEncoder(categories='auto', drop=None, sparse=True)
X = onehotencoder.fit_transform(X).toarray()
X = X[:, 1:]
# Splitting the dataset into training and testing set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 123)
#Feature Scalling
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)
# Part 2: Make the Artifical Neural Network (ANN)
#Import the Keras library and packages
import keras
from keras.models import Sequential
from keras.layers import Dense

#Initialising the ANN
classifier = Sequential ()
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
#Adding the second hidden layer
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
#Adding the output layer
classifier.add(Dense(output = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))

Answer 1

尝试以下更改：

classifier.add(Dense(6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
#Adding the second hidden layer
classifier.add(Dense(6, kernel_initializer = 'uniform', activation = 'relu'))
#Adding the output layer
classifier.add(Dense(1, kernel_initializer = 'uniform', activation = 'sigmoid'))

让我知道！