TypeError：无法使用灵活类型执行缩减

Question

我一直在使用scikit-learn库。我试图在scikit-learn库中使用高斯朴素贝叶斯模块，但我遇到了以下错误。 TypeError：无法使用弹性类型执行缩减

下面是代码段。

training = GaussianNB() 
training = training.fit(trainData, target) 
prediction = training.predict(testData) 

这是目标

['ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'ALL', 'AML', 'AML', 'AML', 'AML', 'AML', 'AML', 'AML', 'AML', 'AML', 'AML', 'AML'] 

这是trainData

[['-214' '-153' '-58' ..., '36' '191' '-37'] 
['-139' '-73' '-1' ..., '11' '76' '-14'] 
['-76' '-49' '-307' ..., '41' '228' '-41'] 
..., 
['-32' '-49' '49' ..., '-26' '133' '-32'] 
['-124' '-79' '-37' ..., '39' '298' '-3'] 
['-135' '-186' '-70' ..., '-12' '790' '-10']] 

下面是堆栈跟踪

Traceback (most recent call last): 
File "prediction.py", line 90, in <module> 
    gaussianNaiveBayes() 
File "prediction.py", line 76, in gaussianNaiveBayes 
    training = training.fit(trainData, target) 
File "/Library/Python/2.7/site-packages/sklearn/naive_bayes.py", line 163, in fit 
    self.theta_[i, :] = np.mean(Xi, axis=0) 
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/ core/fromnumeric.py", line 2716, in mean 
    out=out, keepdims=keepdims) 
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/core/_methods.py", line 62, in _mean 
    ret = um.add.reduce(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims) 
TypeError: cannot perform reduce with flexible type 

Answer 1

它看起来像你的 'trainData' 是名单字符串：

['-214' '-153' '-58' ..., '36' '191' '-37'] 

将您的'trainData'更改为数字类型。

import numpy as np 
np.array(['1','2','3']).astype(np.float)