Linear Decoders
From Ufldl
(→Sparse Autoencoder Recap) |
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While some datasets like MNIST fit well with this scaling of the output, this can sometimes be awkward to satisfy. For example, if one uses PCA whitening, the input is | While some datasets like MNIST fit well with this scaling of the output, this can sometimes be awkward to satisfy. For example, if one uses PCA whitening, the input is | ||
no longer constrained to <math>[0,1]</math> and it's not clear what the best way is to scale the data to ensure it fits into the constrained range. | no longer constrained to <math>[0,1]</math> and it's not clear what the best way is to scale the data to ensure it fits into the constrained range. | ||
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| + | 【初译】： | ||
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| + | 对于 <math>f(z^{(3)})</math>采用一个S型激励函数后，因S型函数输出值域为 <math>[0,1]</math>，需限制输入的范围为 <math>[0,1]</math>。有一些数据组，例如MNIST手写数字库中其输入输出范围符合极佳，但这种情况难以满足。例如，若采用PCA白化，输入将不再限制于 <math>[0,1]</math>，虽可通过缩放数据来确保其符合特定范围内，显然，这不是最好的方式。 | ||
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| + | 【一校】： | ||
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| + | S型激励函数输出范围是<math>[0,1]</math>，当<math>f(z^{(3)})</math>采用该激励函数时，就要对输入限制或缩放，使其位于<math>[0,1]</math>范围中。一些数据集，比如MNIST，能方便将输出缩放到[0,1]中，但是在输入方面，很难满足要求。比如，PCA白化处理的输入并不满足<math>[0,1]</math>范围要求，也不清楚是否有最好的办法可以将数据缩放到特定范围中。 | ||
== Linear Decoder == | == Linear Decoder == | ||
