In celehs/KESER: Knowledge Extraction via Sparse Embedding Regression (KESER)

library(data.table)
library(wordcloud)

dir <- "https://github.com/celehs/KESER/raw/master/rdata/"
dict <- readRDS(url(paste0(dir, "dictionary.rds"), "rb"))

up1 <- merge(dict, fread("up_rate_1.csv"), all.y = TRUE)
up2 <- merge(dict, fread("up_rate_2.csv"), all.y = TRUE)
up4 <- merge(dict, fread("up_rate_4.csv"), all.y = TRUE)
up8 <- merge(dict, fread("up_rate_8.csv"), all.y = TRUE)

up1.coef <- up1[, 3:4]
up2.coef <- up2[, 3:4]
up4.coef <- up4[, 3:4]
up8.coef <- up8[, 3:4]
names(up1.coef) <- paste0("up1.", names(up1)[3:4])
names(up2.coef) <- paste0("up2.", names(up2)[3:4])
names(up4.coef) <- paste0("up4.", names(up4)[3:4])
names(up8.coef) <- paste0("up8.", names(up8)[3:4])

DF <- cbind(up1[, 1:2], 
      up1.coef,
      up2.coef,
      up4.coef,
      up8.coef)
fwrite(DF, "results.csv")

celehs/KESER documentation built on April 7, 2022, 9:35 a.m.