def __init__(self):
self.g = Group()
self.input = FileInOut()
self.classes = self.input.readClasses("KNN")
# self.classes = self.input.readClasses("NB")
self.docVectorList, self.vectorsIds = self.input.readDocsVector()
self.wordFormer = FormWords()
def set_tokens(self):
input = FileInOut()
dictionary = input.readDic()
M = len(dictionary)
print("M :" + str(M))
T = 755440
return T, M
def __init__(self):
self.input = FileInOut()
self.wordFormer = FormWords()
self.constants = ConstantVars()
self.dictionary = dict()
self.posting_list = np.array([dict() for j in range(150000)])
self.dicIndex = 0
self.docIndex = 0
self.c = 0
def set_cf_dictionary(self):
input = FileInOut()
postings = input.readPostingList()
cfis = {}
for i in range(len(postings) - 1):
cfis[i] = 0
for j in range(len(postings[i]) - 1):
cfis[i] += len(postings[i][j])
self.cfDic = sorted(cfis.items(),
key=lambda cfis: cfis[1],
reverse=True)
cfis.clear()
def __init__(self):
self.input = FileInOut()
self.Dic = self.input.readDic()
self.DocID_file = self.input.readDocID()
self.posting_file = self.input.readPostingList()
self.wordFormer = FormWords()
self.constants = ConstantVars()
self.relatedDocs = []
self.notRelatedDocs = []
self.relatedDocsPos = []
self.notRelatedDocsPos = []
self.notRelatedCounts = 0
def __init__(self):
self.inOut = FileInOut()
self.df = dict()
v, d = self.inOut.readDocsVector()
for i in range(1, 38729):
for j in v:
if i in j.keys():
self.df.setdefault(str(i), []).append(j[i])
else:
self.df.setdefault(str(i), []).append(0)
self.df = pd.DataFrame(self.df)
self.df.index=d
print('phase 1 completed')
def __init__(self, algorithm):
self.train_data = Train_data()
print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
self.input = FileInOut()
self.k = 5
# self.train_data = self.input.N
self.docVectorList, self.vectorsIds = self.input.readDocsVector()
print("222222222222222222222")
self.trainVectorList, self.trainvectorsIds = self.input.readTrainDocsVector(
)
print("33333333333333333333333333333")
self.num_ov_results = 100
self.gp = Group([7745])
print("ta ghable knn umaaaaaaad")
self.classes = self.KNN()
def __init__(self):
self.inOut = FileInOut()
self.clusters = self.inOut.readClusters()
self.g = Group()
self.similarity = Similiarity()
self.v, self.d = self.inOut.readDocsVector()
def __init__(self):
self.input = FileInOut()
self.N = self.input.N