Python的錯誤不支持的操作類型

我想寫樸素貝葉斯分類器，我不斷收到此錯誤：Python的錯誤不支持的操作類型

Traceback (most recent call last): 
File "<pyshell#30>", line 1, in <module> 
import naive_assignment 
File "C:\Python27\naive_assignment.py", line 655, in <module> 
main() 
File "C:\Python27\naive_assignment.py", line 650, in main 
pans.append(p.classify(row)) 
File "C:\Python27\naive_assignment.py", line 597, in classify 
less50Kcp = less50Kcp + self.less_cat_probs.get(query[4]) 
TypeError: unsupported operand type(s) for +: 'float' and 'NoneType'

我柔夷花序知道如何解決它，因爲大部分的修復在那裏說一些回報但已經在代碼中。

def classify(self, query): 

    less50Knp = 0.0 
    less50Kcp = 0.0 
    great50Knp = 0.0 
    great50Kcp = 0.0 

    less50Knp = less50Knp +self.less_num_prob_dist(float(query[1])/100) 
    less50Knp = less50Knp + self.less_num_prob_dist(float(query[3])/100) 
    less50Knp = less50Knp + self.less_num_prob_dist(float(query[5])/100) 
    less50Knp = less50Knp + self.less_num_prob_dist(float(query[11])/100) 
    less50Knp = less50Knp + self.less_num_prob_dist(float(query[12])/100) 
    less50Knp = less50Knp + self.less_num_prob_dist(float(query[13])/100) 

    less50Kcp = less50Kcp + self.less_cat_probs.get(query[2]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[4]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[6]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[7]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[8]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[9]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[10]) 
    less50Kcp = less50Kcp + self.less_cat_probs.get(query[14]) 



    less50K_prob = less50Kcp * less50Knp 

    great50Knp = great50Knp + self.great_num_prob_dist(float(query[1])/100) 
    great50Knp = great50Knp + self.great_num_prob_dist(float(query[3])/100) 
    great50Knp = great50Knp + self.great_num_prob_dist(float(query[5])/100) 
    great50Knp = great50Knp + self.great_num_prob_dist(float(query[11])/100) 
    great50Knp = great50Knp + self.great_num_prob_dist(float(query[12])/100) 
    great50Knp = great50Knp + self.great_num_prob_dist(float(query[13])/100) 

    great50Kcp = great50Kcp + self.great_cat_probs.get(query[2]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[4]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[6]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[7]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[8]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[9]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[10]) 
    great50Kcp = great50Kcp + self.great_cat_probs.get(query[14]) 


    great50K_prob = great50Kcp * great50Knp 

    if less50K_prob > great50K_prob: 
     return ' <=50K' 

    elif less50K_prob < great50K_prob: 
     return ' >50K' 

    else: 
     return 'unknown'

我知道這不是編碼它的最好方法。調用此功能主要是：

def main(): 

data = getInputData('./trainingset.txt') 
test = getInputData('./queries.txt') 

p = nbayes(data) 
p.train() 

pans = [] 

for row in test: 
    pans.append(p.classify(row)) 
print("n-bayes") 
print(pans) 


main()

任何人都不會有想法如何解決這一問題？

來源

2012-04-16 Droid_Interceptor