multi_grid {creditmodel}

Arrange list of plots into a grid

Description

Plot multiple ggplot-objects as a grid-arranged single plot.

Usage

multi_grid(..., grobs = list(...), nrow = NULL, ncol = NULL)

Arguments

...

Other parameters.

grobs

A list of ggplot-objects to be arranged into the grid.

nrow

Number of rows in the plot grid.

ncol

Number of columns in the plot grid.

Details

This function takes a list of ggplot-objects as argument. Plotting functions of this package that produce multiple plot objects (e.g., when there is an argument facet.grid) usually return multiple plots as list.

Value

An object of class gtable.

Examples

library(ggplot2)
sub = cv_split(UCICreditCard, k = 30)[[1]]
dat = UCICreditCard[sub,]
dat = re_name(dat, "default.payment.next.month", "target")
dat = data_cleansing(dat, target = "target", obs_id = "ID",
occur_time = "apply_date", miss_values = list("", -1))
dat = process_nas(dat)
train_test = train_test_split(dat, split_type = "OOT", prop = 0.7,
                                occur_time = "apply_date")
dat_train = train_test$train
dat_test = train_test$test
x_list = c("PAY_0", "LIMIT_BAL", "PAY_AMT5", "PAY_3", "PAY_2")
Formula = as.formula(paste("target", paste(x_list, collapse = ' + '), sep = ' ~ '))
set.seed(46)
lr_model = glm(Formula, data = dat_train[, c("target", x_list)], family = binomial(logit))

dat_train$pred_LR = round(predict(lr_model, dat_train[, x_list], type = "response"), 5)
dat_test$pred_LR = round(predict(lr_model, dat_test[, x_list], type = "response"), 5)
# model evaluation
p1 =  ks_plot(train_pred = dat_train, test_pred = dat_test, target = "target", score = "pred_LR")
p2 =  roc_plot(train_pred = dat_train, test_pred = dat_test, target = "target", score = "pred_LR")
p3 =  lift_plot(train_pred = dat_train, test_pred = dat_test, target = "target", score = "pred_LR")
p4 = score_distribution_plot(train_pred = dat_train, test_pred = dat_test,
target = "target", score = "pred_LR")
p_plots= multi_grid(p1,p2,p3,p4)
plot(p_plots)