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from sklearn.linear_model import LogisticRegression
names = ['Fiscal Year', 'Fk Customer Map Id', 'Open Amount Norm',
'Payment Terms', 'Job Id', 'Current Dispute Amount',
'Actual Open Amount', 'Currency', 'Customer Name', 'Payment Terms Day',
'delay']
array = value.values
#Split the data into input and target
X = array[:,0:10]
Y = array[:,10]
#Feature extraction
model = LogisticRegression()
rfe = RFE(model, 3)
fit = rfe.fit(X, Y)
print("Num Features: %d"% fit.n_features_)
print("Selected Features: %s"% fit.support_)
print("Feature Ranking: %s"% fit.ranking_)
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