dr_measure: A measure of kNN of original and dimension reduced data

In talegari/sidekicks: A Misc Set of Functions for Data Analysis

Description

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.

Usage

dr_measure(ldData, d, measure = "jaccard", ...)

Arguments

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 kNN

Details

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

Examples

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))

talegari/sidekicks documentation built on May 30, 2019, 8:40 a.m.