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plot_vars
is used for independent variables with target variable ploting.
get_plots
can loop through plots for all specified independent variables.
get_plots(dat_train, dat_test = NULL, x_list = NULL, target = NULL,
ex_cols = NULL, breaks_list = NULL, pos_flag = NULL,
occur_time = NULL, equal_bins = FALSE, best = TRUE, g = 20,
tree_control = NULL, bins_control = NULL, plot_show = TRUE,
save_data = FALSE, file_name = NULL, parallel = FALSE,
g_width = 8, dir_path = tempdir())plot_vars(dat_train, x, dat_test = NULL, target = "target",
g_width = 8, breaks_list = NULL, pos_flag = list("1", 1, "bad",
"positive"), occur_time = NULL, equal_bins = FALSE, best = TRUE,
g = 20, tree_control = NULL, bins_control = NULL,
plot_show = TRUE, save_data = FALSE, dir_path = tempdir())
A data.frame with independent variables and target variable.
A data.frame of test data. Default is NULL.
Names of independent variables.
The name of target variable.
A list of excluded variables. Regular expressions can also be used to match variable names. Default is NULL.
A table containing a list of splitting points for each independent variable. Default is NULL.
Value of positive class, Default is "1".
The name of the variable that represents the time at which each observation takes place.
Logical, generates initial breaks for equal frequency binning.
Logical, merge initial breaks to get optimal breaks for binning.
Number of initial breakpoints for equal frequency binning.
Parameters of using Decision Tree to segment initial breaks. See detials: get_tree_breaks
Parameters used to control binning. See detials: select_best_class
, select_best_breaks
Logical, show model performance in current graphic device. Default is FALSE.
Logical, save results in locally specified folder. Default is FALSE.
The name for periodically saved data file. Default is NULL.
Logical, parallel computing. Default is FALSE.
The width of graphs.
The path for periodically saved graphic files.
The name of an independent variable.
# NOT RUN {
train_test <- train_test_split(UCICreditCard[1:1000,], split_type = "Random",
prop = 0.8, save_data = FALSE)
dat_train = train_test$train
dat_test = train_test$test
get_plots(dat_train[, c(8, 26)], dat_test = dat_test[, c(8, 26)],
target = "default.payment.next.month")
# }
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