def getTrainSenteceVec(type):
if type == TRAINTYPE:
data = dbConnect.getData(begin=0, end=9000)
elif type == TESTTYPE:
data = dbConnect.getData(begin=9000, end=11000)
return getVec(data)
def getLongRecord(type):
if type == TRAINTYPE:
longData = dbConnect.getData(begin=0, end=9000)
elif type == TESTTYPE:
longData = dbConnect.getData(begin=9000, end=6000)
X_train, y_train, seq_len_train = getSplitVec(longData)
X_train_noh, y_train_noh, seq_len_train_noh = getVec(longData)
return X_train, y_train, seq_len_train, X_train_noh, y_train_noh, seq_len_train_noh
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
# write the sql query here.
query = "select * from customer"
#pass the sql query to the getData method and store the results in `data` variable.
data = getData(query)
print("data: ",data)
dispatcher.utter_message(text="Hello World!",json_message=data)
return []
def buildModel():
# 所有词集合，包括重复词
# allSentences = []
data = dbConnect.getData(begin=0, end=50000, type=2)
sentences = []
for x in data:
# line = re.sub(r_imdb, '', str(x[1]))
result = x[1].split(' ')
# allSentences.extend(result)
sentences.append(result)
# min_count指定了需要训练词语的最小出现次数，默认为5
# size指定了训练时词向量维度，默认为100
# worker指定了完成训练过程的线程数，默认为1不使用多线程。只有注意安装Cython的前提下该参数设置才有意义
model = Word2Vec(sentences, min_count=2, size=EMBEDDING_DIM)
# 保存模型
model.save("word2vecModel/imdb_word2vecModel")
def buildModel():
# 所有词集合，包括重复词
# allSentences = []
data = dbConnect.getData(begin=0, end=22000)
sentences = []
for x in data:
line = re.sub(r, '', str(x[1]))
se_list = jieba.cut(line, cut_all=True)
result = list(se_list)
# allSentences.extend(result)
sentences.append(result)
# min_count指定了需要训练词语的最小出现次数，默认为5
# size指定了训练时词向量维度，默认为100
# worker指定了完成训练过程的线程数，默认为1不使用多线程。只有注意安装Cython的前提下该参数设置才有意义
model = Word2Vec(sentences, min_count=1, size=EMBEDDING_DIM)
# 保存模型
model.save("word2vecModel/word2vecModel")
reload(sys)
sys.setdefaultencoding('utf-8')
# 正则过滤表达式
r = "（|）|；|、|！|，|。|\*|？|~|\<|\>|\s+"
maxSeqLength = 250
EMBEDDING_DIM = 10
TRAINTYPE = 1
TESTTYPE = 0
MAXREVLEN = 6
SENTLENGTH = 20
testdata = longData = dbConnect.getData(begin=28000, end=400)
#词向量模型训练函数
def buildModel():
# 所有词集合，包括重复词
# allSentences = []
data = dbConnect.getData(begin=0, end=22000)
sentences = []
for x in data:
line = re.sub(r, '', str(x[1]))
se_list = jieba.cut(line, cut_all=True)
result = list(se_list)
# allSentences.extend(result)