我正在尝试确定以“ ing”或“ ed”结尾的单词。计算条件频率分布，其中条件为['政府'，'爱好']，事件为“ ing”或“ ed”。将条件频率分布存储在变量inged_cfd中。
下面是我的代码：-
from nltk.corpus import brown
import nltk
genre_word = [ (genre, word.lower())
for genre in ['government', 'hobbies']
for word in brown.words(categories = genre) if (word.endswith('ing') or word.endswith('ed')) ]
genre_word_list = [list(x) for x in genre_word]
for wd in genre_word_list:
if wd[1].endswith('ing'):
wd[1] = 'ing'
elif wd[1].endswith('ed'):
wd[1] = 'ed'
inged_cfd = nltk.ConditionalFreqDist(genre_word_list)
inged_cfd.tabulate(conditions = ['government', 'hobbies'], samples = ['ed','ing'])
我想以表格格式输出为，使用上面的代码，我得到的输出为：-
ed ing
government 2507 1605
hobbies 2561 2262
实际输出为：-
ed ing
government 2507 1474
hobbies 2561 2169
请解决我的问题，并帮助我获得准确的输出。
答案 0 :(得分：3)
需要排除停用词。同样，在检查有条件的末端时，将外壳降低。工作代码如下：
from nltk.corpus import brown
from nltk.corpus import stopwords
stop_words = set(stopwords.words('english'))
genre_word = [ (genre, word.lower())
for genre in brown.categories() for word in brown.words(categories=genre) if (word.lower().endswith('ing') or word.lower().endswith('ed')) ]
genre_word_list = [list(x) for x in genre_word]
for wd in genre_word_list:
if wd[1].endswith('ing') and wd[1] not in stop_words:
wd[1] = 'ing'
elif wd[1].endswith('ed') and wd[1] not in stop_words:
wd[1] = 'ed'
inged_cfd = nltk.ConditionalFreqDist(genre_word_list)
inged_cfd.tabulate(conditions = cfdconditions, samples = ['ed','ing'])
答案 1 :(得分：3)
在两个地方都使用相同的cfdconditions变量会造成问题。实际上，在python中，所有内容都可以用作对象引用，因此，当您第一次使用cfdconditions时，传递给cdev_cfd.tabulate时它可能会更改，而下次传递时，它会作为更改后的对象传递。如果再初始化一个列表，然后将该列表传递给第二个调用，则更好。
这是我的修改
from nltk.corpus import brown
from nltk.corpus import stopwords
def calculateCFD(cfdconditions, cfdevents):
stop_words= stopwords.words('english')
at=[i for i in cfdconditions]
nt = [(genre, word.lower())
for genre in cfdconditions
for word in brown.words(categories=genre) if word not in stop_words and word.isalpha()]
cdv_cfd = nltk.ConditionalFreqDist(nt)
cdv_cfd.tabulate(conditions=cfdconditions, samples=cfdevents)
nt1 = [(genre, word.lower())
for genre in cfdconditions
for word in brown.words(categories=genre) ]
temp =[]
for we in nt1:
wd = we[1]
if wd[-3:] == 'ing' and wd not in stop_words:
temp.append((we[0] ,'ing'))
if wd[-2:] == 'ed':
temp.append((we[0] ,'ed'))
inged_cfd = nltk.ConditionalFreqDist(temp)
a=['ed','ing']
inged_cfd.tabulate(conditions=at, samples=a)
希望有帮助！
答案 2 :(得分：0)
我使用了解决方案，但仍然无法通过一些测试。 2个测试用例仍然失败。
对于失败的测试用例，我的输出是：
good bad better
adventure 39 9 30
fiction 60 17 27
mystery 45 13 29
science_fiction 14 1 4
ed ing
adventure 3281 1844
fiction 2943 1767
mystery 2382 1374
science_fiction 574 293
和
many years
adventure 24 32
fiction 29 44
science_fiction 11 16
ed ing
adventure 3281 1844
fiction 2943 1767
science_fiction 574 293
我的代码是
def calculateCFD(cfdconditions, cfdevents):
# Write your code here
from nltk.corpus import brown
from nltk import ConditionalFreqDist
from nltk.corpus import stopwords
stopword = set(stopwords.words('english'))
cdev_cfd = [ (genre, word.lower()) for genre in cfdconditions for word in brown.words(categories=genre) if word.lower() not in stopword]
cdev_cfd = [list(x) for x in cdev_cfd]
cdev_cfd = nltk.ConditionalFreqDist(cdev_cfd)
a = cdev_cfd.tabulate(condition = cfdconditions, samples = cfdevents)
inged_cfd = [ (genre, word.lower()) for genre in cfdconditions for word in brown.words(categories=genre) if (word.lower().endswith('ing') or word.lower().endswith('ed')) ]
inged_cfd = [list(x) for x in inged_cfd]
for wd in inged_cfd:
if wd[1].endswith('ing') and wd[1] not in stopword:
wd[1] = 'ing'
elif wd[1].endswith('ed') and wd[1] not in stopword:
wd[1] = 'ed'
inged_cfd = nltk.ConditionalFreqDist(inged_cfd)
b = inged_cfd.tabulate(conditions = sorted(cfdconditions), samples = ['ed','ing'])
return(a,b)
如果任何人都可以提供对此的解决方案，那将有很大的帮助。 谢谢
答案 3 :(得分：0)
预期输出为-
many years
fiction 29 44
adventure 24 32
science_fiction 11 16
ed ing
fiction 2943 1767
adventure 3281 1844
science_fiction 574 293
和
good bad better
adventure 39 9 30
fiction 60 17 27
science_fiction 14 1 4
mystery 45 13 29
ed ing
adventure 3281 1844
fiction 2943 1767
science_fiction 574 293
mystery 2382 1374
答案 4 :(得分：0)
我使用了这种方法，它具有更少的代码行和更快的速度
from nltk.corpus import brown
from nltk.corpus import stopwords
stop_words = set(stopwords.words('english'))
cdev_cfd = nltk.ConditionalFreqDist([(genre, word.lower()) for genre in cfdconditions
for word in brown.words(categories=genre) if word.lower() not in stop_words])
inged_cfd = nltk.ConditionalFreqDist([(genre, word[-3:].lower() if word.lower().endswith('ing') else word[-2:].lower())
for genre in conditions for word in brown.words(categories=genre)
if word.lower() not in stop_words and (word.lower().endswith('ing') or word.lower().endswith('ed'))])
cdev_cfd.tabulate(conditions=conditions, samples=cfdevents)
inged_cfd.tabulate(conditions=conditions, samples=['ed','ing'])
答案 5 :(得分：-1)
from nltk.corpus import stopwords,brown
def calculateCFD(cfdconditions, cfdevents):
# Write your code here
stop_words=set(stopwords.w`enter code here`ords("english"))
list1=[(genre,word.lower()) for genre in cfdconditions for word in brown.words(categories=genre) if word.lower() not in stop_words]
cfd1=nltk.ConditionalFreqDist(list1)
cfd1_tabulate=cfd1.tabulate(conditions=cfdconditions,samples=cfdevents)
#print(cfd1_tabulate)
list2=[[genre,word.lower()] for genre in cfdconditions for word in brown.words(categories=genre) if word.lower() not in stop_words if (word.lower().endswith("ed") or word.lower().endswith("ing"))]
for elem in list2:
if elem[1].endswith("ed"):
elem[1]="ed"
else:
elem[1]="ing"
cfd2=nltk.ConditionalFreqDist(list2)
cfd2_tabulate=cfd2.tabulate(conditions=cfdconditions,samples=["ed","ing"])
#print(cfd2_tabulate)
return cfd1_tabulate,cfd2_tabulate