TypeError:fit()缺少1个必需的位置参数:"y" [英] TypeError: fit() missing 1 required positional argument: 'y'

问题描述

我正在尝试使用高斯朴素贝叶斯分类器"预测经济周期.

I am trying to predict economic cycles using Gaussian Naive Bayes "Classifier".

数据(输入X):

             SPY    Interest Rate    Unemployment   Employment  CPI
Date                    
1997-01-02   56.05     7.82            9.7           3399.9     159.100
1997-02-03   56.58     7.65            9.8           3402.8     159.600
1997-03-03   54.09     7.90            9.9           3414.7     160.000

目标(输出Y):

    Economy
0   Expansion
1   Expansion
2   Expansion
3   Expansion

下面是我的代码:

from sklearn.naive_bayes import GaussianNB
from sklearn import metrics
from sklearn.cross_validation import train_test_split
X = data
Y = target
model = GaussianNB
X_train, X_test, Y_train, Y_test = train_test_split(X,Y)
model.fit(X_train, Y_train)

下面是错误:

TypeError                                 Traceback (most recent call last)
<ipython-input-132-b0975752a19f> in <module>()
  6 model = GaussianNB
  7 X_train, X_test, Y_train, Y_test = train_test_split(X,Y)
  ----> 8 model.fit(X_train, Y_train)

  TypeError: fit() missing 1 required positional argument: 'y'

我做错了什么?我该如何解决/error这个问题?

What am I doing wrong? How can I resolve this issue /error ?

推荐答案

您忘记了括号()":

model = GaussianNB()

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