golf_federated.server.process.strategy.evaluation package

Submodules

golf_federated.server.process.strategy.evaluation.base module

class golf_federated.server.process.strategy.evaluation.base.BaseEval(name: str, question_type: str, positive: bool, target: float, convergence: float = 0.001)[source]

Bases: object

Evaluation strategy base class.

abstract eval(target: numpy.ndarray, prediction: numpy.ndarray)[source]

Abstract method for calculation of evaluation metrics.

Args:

target (numpy.ndarray): Ground truth. prediction (numpy.ndarray): Prediction result.

get_record() → List[source]

Get the evaluation record.

Returns:

List: Evaluation record.

reach_convergence() → bool[source]

Judge whether convergence.

Returns:

Bool: Whether convergence.

reach_target() → bool[source]

Judge whether the target is reached.

Returns:

Bool: Whether the target is reached.

golf_federated.server.process.strategy.evaluation.classification module

class golf_federated.server.process.strategy.evaluation.classification.Accuracy(target)[source]

Bases: golf_federated.server.process.strategy.evaluation.base.BaseEval

Accuracy of classification problems, inheriting from BaseEval class.

eval(target: numpy.ndarray, prediction: numpy.ndarray) → float[source]

Calculation of evaluation metric.

Args:

target (numpy.ndarray): Ground truth. prediction (numpy.ndarray): Prediction result.

Returns:

Float: Accuracy.

golf_federated.server.process.strategy.evaluation.function module

golf_federated.server.process.strategy.evaluation.function.accuracy(target: numpy.ndarray, prediction: numpy.ndarray) → float[source]

Calculation of Avvuracy.

Args:

target (numpy.ndarray): Ground truth. prediction (numpy.ndarray): Prediction result.

Returns:

Float: Accuracy.

golf_federated.server.process.strategy.evaluation.function.mse(target: numpy.ndarray, prediction: numpy.ndarray) → float[source]

Calculation of mse.

Args:

target (numpy.ndarray): Ground truth. prediction (numpy.ndarray): Prediction result.

Returns:

Float: MSE.

golf_federated.server.process.strategy.evaluation.regression module

class golf_federated.server.process.strategy.evaluation.regression.MSE(target)[source]

Bases: golf_federated.server.process.strategy.evaluation.base.BaseEval

Mean squared error of regression problems, inheriting from BaseEval class.

eval(target: numpy.ndarray, prediction: numpy.ndarray) → float[source]

Calculation of evaluation metric.

Args:

target (numpy.ndarray): Ground truth. prediction (numpy.ndarray): Prediction result.

Returns:

Float: MSE.

Module contents