# needs Rtsne and ggplot2
#' test several perplexity options for tSNE and plot
#' @param perplexities list of perplexities to test
#' @param data data to perform tsne on
find_optimal_p_tSNE <- function(perplexities, data) {
for (p in perplexities) {
tsne_out <- Rtsne(as.matrix(train), perplexity = p)
plot(tsne_out$Y)
}
}
#---------------------------------------------------------
# needs Rtsne
#' run tSNE algorithm and return data frame of (x,y) coordinates
#' @param data data to perform tsne on
#' @param optimal_p perplexity
run_tSNE <- function(data, optimal_p) {
all_tsne_out <- Rtsne(as.matrix(data), perplexity = optimal_p)
tsne_coords <- as.data.frame(all_tsne_out$Y)
return(tsne_coords)
}
#---------------------------------------------------------------------
# PCA
#' @param data data to run PCA on
# returns matrix of (x,y) coordinates
run_PCA <- function(data) {
res <- prcomp(data)$x
return(res[,c(1,2)])
}
#----------------------------------------------------------------
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