plot_evaluation.list {Coxmos}

plot_evaluation.list

Description

Run the function "plot_evaluation" for a list of results. More information in "?plot_evaluation".

Usage

plot_evaluation.list(
  lst_eval_results,
  evaluation = "AUC",
  pred.attr = "mean",
  y.min = NULL,
  type = "both",
  round_times = FALSE,
  decimals = 2,
  title = NULL,
  title_size_text = 15,
  legend_title = "Method",
  legend_size_text = 12,
  x_axis_size_text = 10,
  y_axis_size_text = 10,
  label_x_axis_size = 10,
  label_y_axis_size = 10
)

Arguments

lst_eval_results

List (named) of Coxmos evaluation results from eval_Coxmos_models().

evaluation

Character. Perform the evaluation using the "AUC" or "Brier" metric (default: "AUC").

pred.attr

Character. Way to evaluate the metric selected. Must be one of the following: "mean" or "median" (default: "mean").

y.min

Numeric. Minimum Y value for establish the Y axis value. If y.min = NULL, automatic detection is performed (default: NULL).

type

Character. Plot type. Must be one of the following: "both", "line" or "mean". In other case, "both" will be selected (default: "both").

round_times

Logical. Whether times x value should be rounded (default: FALSE).

decimals

Numeric. Number of decimals to use in round times. Must be a value greater or equal zero (default = 2).

title

Character. Plot title (default: NULL).

title_size_text

Numeric. Text size for legend title (default: 15).

legend_title

Character. Legend title (default: "Method").

legend_size_text

Numeric. Text size for legend title (default: 12).

x_axis_size_text

Numeric. Text size for x axis (default: 10).

y_axis_size_text

Numeric. Text size for y axis (default: 10).

label_x_axis_size

Numeric. Text size for x label axis (default: 10).

label_y_axis_size

Numeric. Text size for y label axis (default: 10).

Value

A list of lst_eval_results length. Each element is a list of three elements. lst_plots: A list of two plots. The evaluation over the time, and the extension adding the mean or median on the right. lst_plot_comparisons: A list of comparative boxplots by t.test, anova, wilcoxon, kruscal. df: Data.frame of evaluation result.

Author(s)

Pedro Salguero Garcia. Maintainer: [e-mail]

Examples

data("X_proteomic")
data("Y_proteomic")
set.seed(123)
index_train <- caret::createDataPartition(Y_proteomic$event, p = .5, list = FALSE, times = 1)
X_train <- X_proteomic[index_train,1:50]
Y_train <- Y_proteomic[index_train,]
X_test <- X_proteomic[-index_train,1:50]
Y_test <- Y_proteomic[-index_train,]
coxEN.model <- coxEN(X_train, Y_train, x.center = TRUE, x.scale = TRUE)
eval_results <- list()
eval_results[["cenROC"]] <- eval_Coxmos_models(lst_models = list("coxEN" = coxEN.model),
X_test = X_test, Y_test = Y_test, pred.method = "cenROC")
eval_results[["survivalROC"]] <- eval_Coxmos_models(lst_models = list("coxEN" = coxEN.model),
X_test = X_test, Y_test = Y_test, pred.method = "survivalROC")
plot_eval_results <- plot_evaluation.list(eval_results)