optimizer.py 文件源码

def score_train_test_split(self, parameters):
        logger.info("Evaluating with test size %s with parameters %s", self.task.test_size, parameters)
        logger.info("Training model ...")
        self.model.set_params(**parameters)
        self.model.fit(self.task.X_train, self.task.y_train)
        logger.info("Training model done !")
        y_pred = self.get_prediction(self.model, self.task.X_test)
        score = self.scorer.scoring_function(self.task.y_test, y_pred)
        logger.info("Score = %s", score)
        result = OptimizationResult(
            task=self.task.name,
            model=str(self.model),
            parameters=parameters,
            score=score,
            scorer_name=self.scorer.name,
            validation_method=self.task.validation_method,
            predictions=y_pred.tolist(),
            random_state=self.task.random_state)
        self.opt_logger.save(result)
        return {'loss': score, 'status': STATUS_OK}