Slide 95
Slide 95 text
ハイパラチューニング
def grid_search(X_train, y_train, X_valid, y_valid):
best_score = 1e10
best_alpha = 100
for alpha in [1e-5, 1e-4, 1e-3, 1e-2, 1e-1]:
:
:
if best_score > valid_score:
best_score = valid_score
best_alpha = alpha
### 追加 ###
# Log parameter and metrics
with mlflow.start_run(run_name=f"Grid Search alpha={alpha}"):
mlflow.log_param("alpha", alpha)
mlflow.log_metric("train_score", train_score)
mlflow.log_metric("valid_score", valid_score)
mlflow.log_param("train_size", X_train.shape[0])
mlflow.log_param("valid_size", X_valid.shape[0])
return best_alpha
ハイパラチューニングのメトリクスを送信
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