plot.interactions: Plot importance of interactions or pairs

In EIX: Explain Interactions in 'XGBoost'

Description

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

Usage

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

Arguments

x	a result from the interactions function.
...	other parameters.

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).

Value

a ggplot object

Examples

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)

EIX documentation built on March 23, 2021, 9:06 a.m.