Supervised learning is tasked with learning a function from labeled training data in order to predict the value of any valid input.
监管学习的任务是学习带标签的训练数据的功能，以便预测任何有效输入的值。
Defining network error as optimum objective function, all parameters are looked as function variables, and an entire-supervised algorithm is studied.
这里将网络的总体误差作为目标函数，以待求的所有参数作为变量，同时调整，构成全监督算法。
It realises controlling function through the synthetic environment factors gathered and detected by single chip microcomputer and supervised by epistasy 486 microcomputer.
它通过单片机对温室综合环境因子采集及上位486微机监控和管理，实现对温室综合环境控制功能。
Semi-supervised learning - Combines both labeled and unlabeled examples to generate an appropriate function or classifier.
半分类学习-将标签与非标签用例劫后生成一个合适的函数或分类器。
Semi-supervised learning - Combines both labeled and unlabeled examples to generate an appropriate function or classifier.
半分类学习-将标签与非标签用例劫后生成一个合适的函数或分类器。
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