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VictorSaenger/split_news.py

Last active October 9, 2019 08:17
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split_news.py
# split into shuffled folds:
#Note that you should edit the class array accordingly: Bias (classes_Bias) or Outlet (classes_All)
sss = StratifiedShuffleSplit(n_splits=1, test_size=0.33) # chose one split to make analysis faster. change it if required
for t, te in sss.split(eAll,classes_All):
# Scale the data with StandardScaler before splitting:
X_train, X_test = scaler.fit_transform(eAll)[t], \
scaler.fit_transform(eAll)[te]
y_train, y_test = classes_All[t]-1,classes_All[te]-1
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