# ===============================================================
# ===============================================================
setwd('C:\\Users\\czh\\Desktop')
library(Matrix)
rm(list=ls())
options(stringsAsFactors = F)
library(ConsensusClusterPlus)
dt <- read.csv("train.csv",header = T,
row.names = 1,
stringsAsFactors = F)
colnames(dt)
head(dt)
# ===============================================================
# ===============================================================
for (i in 1:dim(dt)[2]) {
dt[,i] <- ifelse( dt[,i] > median( dt[,i]), 1, 0)
}
head(dt)
# ===============================================================
# ===============================================================
dt1 <- dt
for (i in 1:dim(dt)[2]) {
col_name1 <- paste0(names(dt)[i], '_low')
dt1$col_name1 <- dt[,i]
dt1$col_name1 <- ifelse(dt1$col_name1 == 0, 1,0)
dt1[paste0(names(dt)[i], '_low')] = dt1$col_name1
dt1$col_name1 <- NULL
col_name2 <- paste0(names(dt)[i], '_high')
dt1$col_name2 <- dt[,i]
dt1$col_name2 <- ifelse(dt1$col_name2 == 1, 1,0)
dt1[paste0(names(dt)[i], '_high')] = dt1$col_name2
dt1$col_name2 <- NULL
}
dt1 <- dt1[,-(1:dim(dt)[2])]
head(dt1)
输入数据
输出数据