Sparse Principal Component Analysis via Random Projections (SPCAvRP)

final_estimator | Computes the leading eigenvector from its support |

project_covariance | Projects the sample covariance |

select_projection | Selects the best projection |

select_projections_subspace | Selects the best projections for the subspace estimation |

SPCAvRP | Computes the leading eigenvector using the SPCAvRP algorithm |

SPCAvRP_deflation | Computes the leading eigenvectors using the modified... |

SPCAvRP_parallel | Parallel implementation of the SPCAvRP algorithm |

SPCAvRP_ranking | Ranks the variables |

SPCAvRP_subspace | Computes the leading eigenspace using the SPCAvRP algorithm... |

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