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CreditDecisionML/LinearSVC.py

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from sklearn.svm import LinearSVC
from sklearn.datasets import make_classification
import numpy as np
from pprint import pprint as prt
x2 = np.random.rand(100)
X, y = make_classification(n_features = 5, random_state = 0)
print(X.shape)
prt(X)
print('\n')
print(len(y))
LSVCClf = LinearSVC(dual = False, random_state = 0, penalty = 'l1',tol = 1e-5)
LSVCClf.fit(X, y)