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## Classes | |

class | CPCACut |

## Defines | |

#define | IGNORE_IN_CLASSLIST |

Preprocessor PCACut performs principial component analysis on the input vectors and keeps only the n eigenvectors with eigenvalues above a certain threshold. |

#define IGNORE_IN_CLASSLIST |

Preprocessor PCACut performs principial component analysis on the input vectors and keeps only the n eigenvectors with eigenvalues above a certain threshold.

On preprocessing the stored covariance matrix is used to project vectors into eigenspace only returning vectors of reduced dimension n. Optional whitening is performed.

This is only useful if the dimensionality of the data is rather low, as the covariance matrix is of size num_feat*num_feat. Note that vectors don't have to have zero mean as it is substracted.

SHOGUN Machine Learning Toolbox - Documentation