Description Usage Arguments Details Examples

The idea is to measure the effectiveness of dimension reduction methods by computing a measure using the nearest neighbors of a point in the original space and the reduced space. Currently, "jaccard" is implemented.

1 | ```
dr_measure(ldData, d, measure = "jaccard", ...)
``` |

`ldData` |
(numeric matrix) Dimension reduced data |

`d` |
('dist' object) Distances between points in the original space |

`measure` |
Currently, "jaccard" is implemented |

`...` |
Additional arguments to be passed to |

The metric used to compute distances on dimension reduced data is always euclidean.

1 2 3 4 5 6 7 8 9 10 11 | ```
d_full <- stats::dist(iris[,1:4])
newData <- stats::cmdscale(d_full)
newData_tsne <- Rtsne::Rtsne(d_full, is_distance = TRUE)[["Y"]]
vec <- dr_measure(newData, d_full, k = 10)
summary(vec)
plot(stats::density(vec))
vec_tsne <- dr_measure(newData_tsne, d_full, k = 10)
summary(vec_tsne)
plot(stats::density(vec_tsne))
``` |

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