This package is the Environment-Based Clustering for Interpretable Predictive Models in High Dimensional Data. First, let's look at a dataset called simdata, which contains simulated data for the package:
> library(eclust)> data("simdata")> dim(simdata)[1] 100 502> simdata[1:5, 1:6] Y E Gene1 Gene2 Gene3 Gene4[1,] -94.131497 0 -0.4821629 0.1298527 0.4228393 0.36643188[2,] 7.134990 0 -1.5216289 -0.3304428 -0.4384459 1.57602830[3,] 1.974194 0 0.7590055 -0.3600983 1.9006443 -1.47250061[4,] -44.855010 0 0.6833635 1.8051352 0.1527713 -0.06442029[5,] 23.547378 0 0.4587626 -0.3996984 -0.5727255 -1.75716775> table(simdata[,"E"]) 0 1 50 50 >
The preceding output shows that the dimension of the data is 100 by 502. Y is a continuous ...
