Furthermore, compared with the general Bayesian classifier ensemble, PEBNC requires less space because there is no need to save parameters of individual classifiers.
此外,与一般的贝叶斯集成分类器相比,PEBNC不必存储成员分类器的参数,空间复杂度大大降低。
Enter and save the various network parameters as required.
输入并保存必要的各种网络参数。
You can save everything you see in a integration test client instance including input values, events, manual emulation values, and configuration parameters.
您可以保存在集成测试客户端实例中看到的所有内容,其中包括输入值、事件、手动模拟值和配置参数。
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