R/method.r

In outqrf: Find the Outlier by Quantile Random Forests

#' @title Plots outqrf
#' @description
#' This function can plot paired boxplot of an "outqrf" object.
#' It helps us to better observe the relationship between the original and predicted values
#' @param x An object of class "outqrf".
#' @param ... other param maybe uesd.
#' @returns A ggplot2 object
#' @export
#' @examples
#' irisWithOutliers <- generateOutliers(iris, seed = 2024)
#' qrf <- outqrf(irisWithOutliers)
#' plot(qrf)
plot.outqrf<- function(x,...) {
    result_df <- data.frame()
    data <- x$Data
    tag <- NULL
    for (i in seq_along(x$outMatrixs)) {
        temp_df <- as.data.frame(x$outMatrixs[[i]][,x$quantiles_type/2])
        if (nrow(result_df) == 0) {
          result_df <- temp_df
        } else {
          result_df <- cbind(result_df, temp_df)
        }
    }
    names(result_df) = names(x$outMatrixs)
    result_df <- dplyr::mutate(result_df,tag = "predicted")
    numeric_features <- names(data)[sapply(data,is.numeric)]
    data <- data[numeric_features]
    data <- dplyr::mutate(data,tag = "observed")
    plot_in <-rbind(result_df,data)
    plot_in_longer<- plot_in|>tidyr::pivot_longer(!tag,names_to ="features",values_to ="value" )
    p<- ggpubr::ggpaired(plot_in_longer, x="tag", y="value",
             fill="tag", palette = "jco",
             line.color = "grey", line.size =0.8, width = 0.4,short.panel.labs = FALSE)+
        ggpubr::stat_compare_means(label = "p.format", paired = TRUE)+ggplot2::theme(legend.position = "none")+ggplot2::facet_wrap(~features, scales = "free")
    return(p)
}