Added kernel svm algorithm code file - #12784
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| class BanditAlgorithm(ABC): | ||
| """Base class for bandit algorithms""" | ||
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| def __init__(self, n_arms): |
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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: n_arms
| self.n_arms = n_arms | ||
| self.reset() | ||
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| def reset(self): |
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Please provide return type hint for the function: reset. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function reset
| self.t = 0 | ||
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| @abstractmethod | ||
| def select_arm(self): |
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Please provide return type hint for the function: select_arm. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function select_arm
| def select_arm(self): | ||
| pass | ||
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| def update(self, arm, reward): |
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Please provide return type hint for the function: update. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: arm
Please provide type hint for the parameter: reward
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function update
| class EpsilonGreedy(BanditAlgorithm): | ||
| """Epsilon-Greedy Algorithm""" | ||
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| def __init__(self, n_arms, epsilon=0.1): |
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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: n_arms
Please provide type hint for the parameter: epsilon
| probs = exp_prefs / np.sum(exp_prefs) | ||
| return np.random.choice(self.n_arms, p=probs) | ||
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| def update(self, arm, reward): |
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Please provide return type hint for the function: update. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: arm
Please provide type hint for the parameter: reward
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function update
| class BanditTestbed: | ||
| """Environment for testing bandit algorithms""" | ||
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| def __init__(self, n_arms=10, true_rewards=None): |
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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: n_arms
Please provide type hint for the parameter: true_rewards
| self.true_rewards = true_rewards | ||
| self.optimal_arm = np.argmax(self.true_rewards) | ||
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| def get_reward(self, arm): |
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Please provide return type hint for the function: get_reward. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: arm
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function get_reward
| """Get noisy reward for pulling an arm""" | ||
| return np.random.normal(self.true_rewards[arm], 1) | ||
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| def run_experiment(self, algorithm, n_steps=1000): |
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Please provide return type hint for the function: run_experiment. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: algorithm
Please provide type hint for the parameter: n_steps
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function run_experiment
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| # Example usage and comparison | ||
| def compare_algorithms(): |
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Please provide return type hint for the function: compare_algorithms. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file machine_learning/Multi-Armed Bandits .py, please provide doctest for the function compare_algorithms
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