python-autosklearn-多进程

最新推荐文章于 2025-05-22 09:35:31 发布

原创

最新推荐文章于 2025-05-22 09:35:31 发布 · 786 阅读

1 ·

CC 4.0 BY-SA版权

本文详细介绍了如何利用Python库autosklearn进行自动化机器学习，并着重探讨了如何配置和实现多进程并行化，以提高模型训练的效率。通过实例展示，读者将了解到如何有效地分配计算资源，提升实验效果。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

import multiprocessing
import shutil
import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
from autosklearn.metrics import accuracy
from autosklearn.classification import AutoSklearnClassifier
from autosklearn.constants import MULTICLASS_CLASSIFICATION

tmp_folder = '/tmp/autosklearn_parallel_2_example_tmp'
output_folder = '/tmp/autosklearn_parallel_2_example_out'


for dir_ in [tmp_folder, output_folder]:
    try:
    	# 递归的删除文件夹下的所有子文件夹和子文件
        shutil.rmtree(dir_)
    except OSError:
        pass


def get_spawn_classifier(X_train, y_train):
    def spawn_classifier(seed, dataset_name):
        """Spawn a subprocess.

        auto-sklearn does not take care of spawning worker processes. This
        function, which is called several times in the main block is a new
        process which runs one instance of auto-sklearn.
        """

        # Use the initial configurations from meta-learning only in one out of
        # the four processes