def _extract(self):
columns = [
'W2VWeight_cosine', 'W2VWeight_euclidean', 'W2VWeight_manhattan'
]
data = map_reduce(self.data, self.calculate, columns, n=4)
for column in columns:
self.data[column] = data[column]
def _extract(self):
columns = [
'TFIDFDistance', 'TFIDFSum_1', 'TFIDFSum_2', 'TFIDFMean_1',
'TFIDFMean_2'
]
data = map_reduce(self.data, self.calculate, columns, n=4)
for column in columns:
self.data[column] = data[column]
def _extract(self):
columns = ['NGramTFIDF_one', 'NGramTFIDF_two', 'NGramTFIDF_three']
data = map_reduce(self.data, self.calculate, columns, n=4)
for column in columns:
self.data[column] = data[column]
def _extract(self):
columns = ['Jaccard', 'Sorensen']
data = map_reduce(self.data, self.calculate, columns, n=4)
for column in columns:
self.data[column] = data[column]
def _extract(self):
columns = self.columns
data = map_reduce(self.data, self.calculate, columns, n=4)
for column in columns:
self.data[column] = data[column]
def _extract(self):
columns = ['SpecialConcurrence']
data = map_reduce(self.data, self.calculate, columns, n=4)
for column in columns:
self.data[column] = data[column]