plot.interactions {EIX} | R Documentation |
This function plots the importance ranking of interactions and pairs in the model.
## S3 method for class 'interactions'
plot(x, ...)
x |
a result from the |
... |
other parameters. |
NOTE: Be careful use of this function with option="pairs"
parameter,
because high gain of pair can be a result of high gain of child variable.
As strong interactions should be considered only these pairs of variables,
where variable on the bottom (child) has higher gain than variable on the top (parent).
a ggplot object
library("EIX")
library("Matrix")
sm <- sparse.model.matrix(left ~ . - 1, data = HR_data)
library("xgboost")
param <- list(objective = "binary:logistic", max_depth = 2)
xgb_model <- xgboost(sm, params = param, label = HR_data[, left] == 1, nrounds = 25, verbose=0)
inter <- interactions(xgb_model, sm, option = "interactions")
inter
plot(inter)
inter <- interactions(xgb_model, sm, option = "pairs")
inter
plot(inter)
library(lightgbm)
train_data <- lgb.Dataset(sm, label = HR_data[, left] == 1)
params <- list(objective = "binary", max_depth = 2)
lgb_model <- lgb.train(params, train_data, 25)
inter <- interactions(lgb_model, sm, option = "interactions")
inter
plot(inter)
inter <- interactions(lgb_model, sm, option = "pairs")
inter
plot(inter)