尝试制作一个天真的贝叶斯分类器但是我不断得到“返回功能不正确”或“缩进不匹配和水平”的错误。非常感谢任何帮助,
这是我的代码片段
if row[2] == 'C1':
self.c1_data.append(row)
else:
self.c2_data.append(row)
#Get relative frequencies from variables
#using the values in A ,B and C to
#return a dictionary
def getCatProbs(self, data):
a_count = 0
b_count = 0
c_count = 0
probs = {}
#For every row in the datafile
for row in data:
#Based on figure increase counts
if row[1] == ">50K":
a_count = a_count + 1
if row[1] == "<=50K":
b_count = b_count + 1
else:
c_count = c_count + 1
probs[">50K"] = float(a_count)/len(data)
probs["<=50K"] = float(b_count)/len(data)
probs['C'] = float(c_count)/len(data)
返回probs
答案 0 :(得分:1)
之后的所有行都缺少空格
试试这个缩进:
#Get relative frequencies from variables
#using the values in A ,B and C to
#return a dictionary
def getCatProbs(self, data):
a_count = 0
b_count = 0
c_count = 0
probs = {}
#For every row in the datafile
for row in data:
#Based on figure increase counts
if row[1] == ">50K":
a_count = a_count + 1
if row[1] == "<=50K":
b_count = b_count + 1
else:
c_count = c_count + 1
probs[">50K"] = float(a_count)/len(data)
probs["<=50K"] = float(b_count)/len(data)
probs['C'] = float(c_count)/len(data)
return probs