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Question

In an abstract sense, the SVD or PCA can be thought of as a way to approximate a ***-dimensional matrix (i.e. a high number of ***) with a a few ***-dimensional matrices.

Answer

In an abstract sense, the SVD or PCA can be thought of as a way to approximate a high-dimensional matrix (i.e. a large number of columns) with a a few low-dimensional matrices.

Question

In an abstract sense, the SVD or PCA can be thought of as a way to approximate a ***-dimensional matrix (i.e. a high number of ***) with a a few ***-dimensional matrices.

Answer

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Question

In an abstract sense, the SVD or PCA can be thought of as a way to approximate a ***-dimensional matrix (i.e. a high number of ***) with a a few ***-dimensional matrices.

Answer

In an abstract sense, the SVD or PCA can be thought of as a way to approximate a high-dimensional matrix (i.e. a large number of columns) with a a few low-dimensional matrices.

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status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|

repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

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