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。
Supervised classifiers use labeled training corpora to build models that predict the label of an input based on specific features of that input.
监督式分类器使用标签训练语料库来构建模型，预测基于特定要素输入的所输入的标签。
Unsupervised learning is used to adjust input weight values and supervised learning is utilized to adjust output weight values.
学习过程中，采用无监督学习算法对输入权重进行调整，采用有监督学习算法对输出权重进行调整。
Semi-Supervised Learning : Input data is a mixture of labelled and unlabelled examples.
半监督学习：输入数据由带标记的和不带标记的组成。
Semi-Supervised Learning: Input data is a mixture of labelled and unlabelled examples.
半监视学习：输入数据由带符号的和不带符号的组成。
Semi-Supervised Learning: Input data is a mixture of labelled and unlabelled examples.
无监督学习：输入数据不带标签或者没有一个已知的结果。
Semi-Supervised Learning: Input data is a mixture of labelled and unlabelled examples.
无监督学习：输入数据不带标签或者没有一个已知的结果。
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