데이터 분석/Python
[Sklearn] ElasticNet
eunki
2021. 5. 13. 23:54
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ElasticNet
l1_ratio (default=0.5)
l1_ratio = 0 (L2 규제만 사용)
l1_ratio = 1 (L1 규제만 사용)
0 < l1_ratio < 1 (L1 and L2 규제의 혼합사용)
from sklearn.linear_model import ElasticNet
ratios = [0.2, 0.5, 0.8]
for ratio in ratios:
elasticnet = ElasticNet(alpha=0.5, l1_ratio=ratio)
elasticnet.fit(x_train, y_train)
pred = elasticnet.predict(x_test)

elsticnet_20 = ElasticNet(alpha=5, l1_ratio=0.2)
elsticnet_20.fit(x_train, y_train)
elasticnet_pred_20 = elsticnet_20.predict(x_test)

elsticnet_80 = ElasticNet(alpha=5, l1_ratio=0.8)
elsticnet_80.fit(x_train, y_train)
elasticnet_pred_80 = elsticnet_80.predict(x_test)

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