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Both sides previous revisionPrevious revision | Last revisionBoth sides next revision | ||
data_mining:neural_network:overfitting [2018/05/10 17:52] – [Weight penalites] phreazer | data_mining:neural_network:overfitting [2018/05/10 17:55] – [Inverted dropout] phreazer | ||
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Line 141: | Line 141: | ||
Layer $l=3$. | Layer $l=3$. | ||
- | $keep.prob = 0.8$ | + | $keep.prob = 0.8$ // probability that unit will be kept |
$d3 = np.random.rand(a3.shape[0], | $d3 = np.random.rand(a3.shape[0], | ||
- | $a3 = np.multiply(a3, | + | $a3 = np.multiply(a3, |
$a3 /= keep.prob$ // e.g. 50 units => 10 units shut off | $a3 /= keep.prob$ // e.g. 50 units => 10 units shut off |