Self-Taught Learning
From Ufldl
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== Overview == | == Overview == | ||
| - | + | Assuming that you have a sufficiently powerful learning algorithm, one of the most reliable | |
| - | to give your | + | ways to get better performance is to give your algorithm more data. This has led to the |
| + | that aphorism that in | ||
machine learning, "sometimes it's not who has the best algorithm that wins; it's | machine learning, "sometimes it's not who has the best algorithm that wins; it's | ||
who has the most data." | who has the most data." | ||
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these models often given good results even if we have only | these models often given good results even if we have only | ||
labeled data (in which case we usually perform the feature learning step using | labeled data (in which case we usually perform the feature learning step using | ||
| - | the labeled data, but ignoring the labels). | + | the labeled data, but ignoring the labels). |
| - | + | ||
== Learning features == | == Learning features == | ||
