simulation/decai/simulation/simulate_bhp_dt.py [79:90]:
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    ])
    d = inj.get(DataLoader)
    (x_train, y_train), (x_test, y_test) = d.load_data()
    c = inj.get(Classifier)
    c.init_model(x_train, y_train)
    score = c.evaluate(x_train, y_train)
    import random

    for _ in range(10):
        i = random.randrange(len(x_train))
        print(f"{i:04d}: {x_train[i]}: {y_train[i]}")
        print(f"Prediction: {c.predict(x_train[i])}")
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simulation/decai/simulation/simulate_titanic_dt.py [79:90]:
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    ])
    d = inj.get(DataLoader)
    (x_train, y_train), (x_test, y_test) = d.load_data()
    c = inj.get(Classifier)
    c.init_model(x_train, y_train)
    score = c.evaluate(x_train, y_train)
    import random

    for _ in range(10):
        i = random.randrange(len(x_train))
        print(f"{i:04d}: {x_train[i]}: {y_train[i]}")
        print(f"Prediction: {c.predict(x_train[i])}")
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