Description Usage Arguments Value

View source: R/feature_extraction.R

Feature extraction by stochastic mds

1 2 3 | ```
seq2feature_mds_stochastic(seqs = NULL, K = 2,
dist_type = "oss_action", max_epoch = 100, step_size = 0.01,
pca = TRUE, tot = 1e-06, return_dist = FALSE, L_set = 1:3)
``` |

`seqs` |
a |

`K` |
the number of features to be extracted. |

`dist_type` |
a character string specifies the dissimilarity measure for two response processes. See 'Details'. |

`max_epoch` |
the maximum number of epochs for stochastic gradient descent. |

`step_size` |
the step size of stochastic gradient descent. |

`pca` |
a logical scalar. If |

`tot` |
the accuracy tolerance for determining convergence. |

`return_dist` |
logical. If |

`L_set` |
length of ngrams considered. |

`seq2feature_mds_stochastic`

returns a list containing

`theta` |
a numeric matrix giving the |

`loss` |
the value of the multidimensional scaling objective function. |

`dist_mat` |
the dissimilary matrix. This element exists only if |

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