def TFIDF(df, word_list):
'''
调用前面写的tfidf算法来训练矩阵
:return: 返回TFIDF矩阵
'''
df = read_file("classification_simple_test.csv", [0])
data = [a[0].split() for a in np.array(df).tolist()]
IDF_list = T.IDF(data, word_list) # 计算idf值
TFIDF_met = np.empty(shape=(len(data), len(word_list)))
for i, record in enumerate(data):
TF_dic = T.TF(record)
for index, word in enumerate(word_list):
TFIDF_met[i][index] = TF_dic.get(word, 0) * IDF_list[index]
return TFIDF_met
def __init__(self, span, d, iterations, index):
self.kspan = span # 共现窗口的长度
self.d = d
self.iteration = iterations
# ---- TF-IDF 初始化 ---- #
docs = dataset.read_sogou()
for i, doc in enumerate(docs):
docs[i] = TFIDF.cut_by_words(doc)
data, self.VSM = TFIDF.create_VSM(docs)
print("Create VSM Over !")
# 生成 IDF
self.idf = TFIDF.IDF(data, self.VSM)
self.tfidf = TFIDF.TF_IDF(data[index], self.VSM, self.idf)
self.keywords_doc = TFIDF.extract_keywords_tfidf(self.tfidf, self.VSM)
print("Got the keywors from the docs !")
