adjusted_dates = future_forcast_dates[:-3]
X_train_confirmed, X_test_confirmed, y_train_confirmed, y_test_confirmed = train_test_split(days_since_1_22, world_cases, test_size=0.1, shuffle=False)
kernel = ['linear', 'rbf']

c = [0.01, 0.1, 1, 10]
gamma = [0.01, 0.1, 1]
epsilon = [0.01, 0.1, 1]
shrinking = [True, False]
svm_grid = {'kernel': kernel, 'C': c, 'gamma' : gamma, 'epsilon': epsilon, 'shrinking' : shrinking}
svm = SVR()
svm_search = RandomizedSearchCV(svm, svm_grid, scoring='neg_mean_squared_error', cv=3, return_train_score=True, n_jobs=-1, n_iter=30, verbose=1)
svm_search.fit(X_train_confirmed, y_train_confirmed)

这什么原因啊，我都搞不懂