问题描述
最近我在python代码上遇到了如下问题：
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.decomposition import LatentDirichletAllocation
from sklearn.pipeline import Pipeline
from sklearn.model_selection import gridsearchcv
from sklearn.naive_bayes import MultinomialNB
import datetime
time_stamp_start = datetime.datetime.Now()
print('Starting time is: {}'.format(time_stamp_start.strftime('%Y.%m.%d-%H:%M:%s')))
data = pd.read_csv('Train_movie.csv')
X_train = data.Message
y_train = data.label
Count = CountVectorizer(stop_words = 'english')
# stop_words,ngram_range=(1,1),max_df=1.0,max_features=None
lda = LatentDirichletAllocation()
#n_components=10,learning_method='batch',learning_decay=.7,learning_offset=10.
mbb = MultinomialNB()
#Before Process
print('Processing Before...')
#Processing
ppl_bayes = Pipeline([('count',Count),('lda',lda),('mbb',mbb)])
param_grid = [{'count__ngram_range':[(1,(1,2),(2,2)],'count__max_df':[0.1,0.5,0.9],'lda__n_components':[7,10,12],'lda__learning_method':['online'],'lda__learning__decay':[.7,.9],'mbb__alpha':[1.0]},{'count__ngram_range':[(1,'lda__learning_method':['batch'],'mbb__alpha':[1.0]}]
print('Processing Now...')
gs_ppl_bayes = gridsearchcv(estimator = ppl_bayes,param_grid = param_grid,scoring = 'accuracy',cv = 5,n_jobs = -1)
print('Processing done!!')
gs_ppl_bayes.fit(X_train,y_train)
print('Mission processing...')
print(gs_ppl_bayes.best_params_)
time_stamp_end = datetime.datetime.Now()
print('Ending time is: {}'.format(time_stamp_end.strftime('%Y.%m.%d-%H:%M:%s')))
我想使用gridsearchcv调整我最好的超参数。很好地显示这些结果：
Starting time is: 2020.08.31-15:15:06
Processing Before...
Processing Now...
Processing done!!
但是，等待了大约4个小时之后，没有其他后续结果！！！有什么问题？我要疯了。
提前谢谢！！伙计们！
解决方法
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