EIX (version 1.2.0)

plot.interactions: Plot importance of interactions or pairs

Description

This function plots the importance ranking of interactions and pairs in the model.

Usage

# S3 method for interactions
plot(x, ...)

Arguments

x

a result from the interactions function.

...

other parameters.

Value

a ggplot object

Details

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).

Examples

# NOT RUN {
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)

# }
# NOT RUN {
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)
# }
# NOT RUN {
# }