Question

我对Python和机器学习非常陌生，下面是我在python 3中的代码，我正在用jupyter nottebook编写python代码。

import random
def splitDataset(dataset, splitRatio):
trainSize = int(len(dataset) * splitRatio)
trainSet = []
copy = list(dataset)
while len(trainSet) < trainSize:
    index = random.randrange(len(copy))
    trainSet.append(copy.pop(index))
return [trainSet, testSet]

import csv
import sys
from langdetect import detect
import random
import math


def loadCsv(filename):
lines = csv.reader(open(filename, "r",encoding='latin1'))
x=0
myList=[]
for line in lines:
    t=line[14]
    try:
        b = detect(t)
        if b=="en":
            myList.insert(x,t)
            x=x+1
    except Exception :
        y=0
return myList


import nltk.classify.util
from nltk.classify import NaiveBayesClassifier 

filename = 'F:\\Study\\Text Mining (GIT)\\sources\\Data.csv'
splitRatio = 0.8
loadCsv(filename)
trainingSet, testSet = splitDataset(myList, splitRatio)

classifier = nltk.NaiveBayesClassifier.train(trainingSet)
print (nltk.classify.util.accuracy(classifier, testSet))

classifier.show_most_informative_features()

在运行abve代码后，出现以下错误

ValueError                                Traceback (most recent call last)
<ipython-input-206-75c0ffc409d5> in <module>()
 10 print(len(testSet))
 11 
 ---> 12 classifier = nltk.NaiveBayesClassifier.train(trainingSet)
 13 print (nltk.classify.util.accuracy(classifier, testSet))
 14 

 f:\python\lib\site-packages\nltk\classify\naivebayes.py in train(cls, 
 labeled_featuresets, estimator)
 195         # Count up how many times each feature value occurred, given
 196         # the label and featurename.
 --> 197         for featureset, label in labeled_featuresets:
 198             label_freqdist[label] += 1
  199             for fname, fval in featureset.items():

 ValueError: too many values to unpack (expected 2)


 trainingSet=[ "Pleasant 10 min walk along the sea front to the Water Bus. restaurants etc. Hotel was comfortable breakfast was good - quite a variety. Room aircon didn't work very well. Take mosquito repelant!", "Really lovely hotel. Stayed on the very top floor and were surprised by a Jacuzzi bath we didn't know we were getting! Staff were friendly and helpful and the included breakfast was great! Great location and great value for money. Didn't want to leave!", 'We stayed here for four nights in October. The hotel staff were welcoming, friendly and helpful. Assisted in booking tickets for the opera. The rooms were clean and comfortable- good shower, light and airy rooms with windows you could open wide. Beds were comfortable. Plenty of choice for breakfast.Spa at hotel nearby which we used while we were there.', 'We stayed here for four nights in October. The hotel staff were welcoming, friendly and helpful. Assisted in booking tickets for the opera. The rooms were clean and comfortable- good shower, light and airy rooms with windows you could open wide. Beds were comfortable. Plenty of choice for breakfast.Spa at hotel nearby which we used while we were there.',.....]

我已经看过以下网站的解决方案，但找不到任何解决方案： ValueError: too many values to unpack (NLTK classifier)

NLTK ValueError: too many values to unpack (expected 2)

http://www.solutionscan.org/220106-python

ValueError : too many values to unpack (expected 2)

NLTK accuracy: "ValueError: too many values to unpack"

Answer 1

您对train（）的输入错误。它期望输入元组列表，其中元组的第一个元素应该是字典。

it-begin()+.data()

def train(cls, labeled_featuresets, estimator=ELEProbDist):
    """
    :param labeled_featuresets: A list of classified featuresets,
        i.e., a list of tuples ``(featureset, label)``.
    """

您可以参考NLTK documentation上的示例并打印出特征集值以了解格式。

朴素贝叶斯分类器值错误Python

1 个答案: