chạy nó báo lỗi nhiều qua e ko thể nào biết cách khắc phục ai chạy được chỉ e với ạ
code

-- coding: utf-8 --

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Created on Thu Sep 17 16:09:21 2015

@author: Dipayan
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from pandas import Series, DataFrame
import pandas as pd
import numpy as np
import nltk
import re
from nltk.stem import WordNetLemmatizer
from sklearn.svm import LinearSVC
from sklearn.metrics import classification_report
import sklearn.metrics
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn import grid_search
from sklearn.linear_model import LogisticRegression

A combination of Word lemmatization + LinearSVC model finally pushes the accuracy score past 80%

traindf = pd.read_json("…/input/train.json")
traindf[‘ingredients_clean_string’] = [’ , ‘.join(z).strip() for z in traindf[‘ingredients’]]
traindf[‘ingredients_string’] = [’ ‘.join([WordNetLemmatizer().lemmatize(re.sub(’[^A-Za-z]’, ’ ', line)) for line in lists]).strip() for lists in traindf[‘ingredients’]]

testdf = pd.read_json("…/input/test.json")
testdf[‘ingredients_clean_string’] = [’ , ‘.join(z).strip() for z in testdf[‘ingredients’]]
testdf[‘ingredients_string’] = [’ ‘.join([WordNetLemmatizer().lemmatize(re.sub(’[^A-Za-z]’, ’ ', line)) for line in lists]).strip() for lists in testdf[‘ingredients’]]

corpustr = traindf[‘ingredients_string’]
vectorizertr = TfidfVectorizer(stop_words=‘english’,
ngram_range = ( 1 , 1 ),analyzer=“word”,
max_df = .57 , binary=False , token_pattern=r’w+’ , sublinear_tf=False)
tfidftr=vectorizertr.fit_transform(corpustr).todense()
corpusts = testdf[‘ingredients_string’]
vectorizerts = TfidfVectorizer(stop_words=‘english’)
tfidfts=vectorizertr.transform(corpusts)

predictors_tr = tfidftr

targets_tr = traindf[‘cuisine’]

predictors_ts = tfidfts

#classifier = LinearSVC(C=0.80, penalty=“l2”, dual=False)
parameters = {‘C’:[1, 10]}
#clf = LinearSVC()
clf = LogisticRegression()

classifier = grid_search.GridSearchCV(clf, parameters)

classifier=classifier.fit(predictors_tr,targets_tr)

predictions=classifier.predict(predictors_ts)
testdf[‘cuisine’] = predictions
testdf = testdf.sort(‘id’ , ascending=True)

testdf[[‘id’ , ‘ingredients_clean_string’ , ‘cuisine’ ]].to_csv(“submission.csv”)