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The translation of the terminology "set" #203

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The translation of the terminology "set" #203

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2 changes: 1 addition & 1 deletion Chapter5/machine_learning_basics.tex
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Expand Up @@ -250,7 +250,7 @@ \subsection{\glsentrytext{experience} $E$}
例如，你有不同宽度和高度的照片的集合，那么不同的照片将会包含不同数量的像素。
因此不是所有的照片都可以表示成相同长度的向量。
\secref{sec:data_types}和\chapref{chap:sequence_modeling_recurrent_and_recursive_nets}将会介绍如何处理这些不同类型的异构数据。
在上述这类情况下，我们不会将\gls{dataset}表示成$m$行的矩阵，而是表示成$m$个元素的结合：$\{\Vx^{(1)},\Vx^{(2)},\dots,\Vx^{(m)}\}$。
在上述这类情况下，我们不会将\gls{dataset}表示成$m$行的矩阵，而是表示成$m$个元素的集合：$\{\Vx^{(1)},\Vx^{(2)},\dots,\Vx^{(m)}\}$。
这种表示方式意味着\gls{example:chap5}向量$\Vx^{(i)}$和$\Vx^{(j)}$可以有不同的大小。

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