基本概念
K折交叉验证用于评估一个模型的泛化性能,那么网格搜索通过调参来提高模型的泛化性能.
简单的网格搜索实现
提前划分好训练集和测试集,简单通过两个for循环寻找最佳参数,评估效果直接使用模型自带的score.
# naive grid search implementation
from sklearn.svm import SVC
X_train, X_test, y_train, y_test = train_test_split(
iris.data, iris.target, random_state=0)
print("Size of training set: {} size of test set: {}".format(
X_train.shape[0], X_test.shape[0]))
best_score = 0
for gamma in [0.001, 0.01, 0.1, 1, 10, 100]:
for C in [0.001, 0.01, 0.1, 1, 10, 100]:
# for each
机器学习
· 2023-03-31
· 291 人浏览
Axuanz
