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Upgrade to Python 3.13 (#11588)

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This commit is contained in:
Christian Clauss
2024-09-30 23:01:15 +02:00
committed by GitHub
parent a7bfa22455
commit 0177ae1cd5
35 changed files with 135 additions and 131 deletions
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8
machine_learning/forecasting/run.py
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@ -28,7 +28,7 @@ def linear_regression_prediction(
input : training data (date, total_user, total_event) in list of float
output : list of total user prediction in float
>>> n = linear_regression_prediction([2,3,4,5], [5,3,4,6], [3,1,2,4], [2,1], [2,2])
>>> abs(n - 5.0) < 1e-6 # Checking precision because of floating point errors
>>> bool(abs(n - 5.0) < 1e-6) # Checking precision because of floating point errors
True
"""
x = np.array([[1, item, train_mtch[i]] for i, item in enumerate(train_dt)])
@ -56,7 +56,7 @@ def sarimax_predictor(train_user: list, train_match: list, test_match: list) ->
)
model_fit = model.fit(disp=False, maxiter=600, method="nm")
result = model_fit.predict(1, len(test_match), exog=[test_match])
return result[0]
return float(result[0])
def support_vector_regressor(x_train: list, x_test: list, train_user: list) -> float:
@ -75,7 +75,7 @@ def support_vector_regressor(x_train: list, x_test: list, train_user: list) -> f
regressor = SVR(kernel="rbf", C=1, gamma=0.1, epsilon=0.1)
regressor.fit(x_train, train_user)
y_pred = regressor.predict(x_test)
return y_pred[0]
return float(y_pred[0])
def interquartile_range_checker(train_user: list) -> float:
@ -92,7 +92,7 @@ def interquartile_range_checker(train_user: list) -> float:
q3 = np.percentile(train_user, 75)
iqr = q3 - q1
low_lim = q1 - (iqr * 0.1)
return low_lim
return float(low_lim)
def data_safety_checker(list_vote: list, actual_result: float) -> bool: