Description Usage Arguments Details Value Examples
View source: R/data_visualization.R
Plot multiple ggplot-objects as a grid-arranged single plot.
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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. |
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.
An object of class gtable.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | 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)
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