#' MetaMetrics – Binary-Classification Performance-Metrics Benchmarking (Stage 2)
#' Copyright (C) 2017-2019 Gürol Canbek
#' This file is licensed under
#'
#' GNU Affero General Public License v3.0, GNU AGPLv3
#'
#' This program is free software: you can redistribute it and/or modify
#' it under the terms of the GNU Affero General Public License as published
#' by the Free Software Foundation, either version 3 of the License, or
#' (at your option) any later version.
#'
#' This program is distributed in the hope that it will be useful,
#' but WITHOUT ANY WARRANTY; without even the implied warranty of
#' MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
#' GNU Affero General Public License for more details.
#'
#' You should have received a copy of the GNU Affero General Public License
#' along with this program. If not, see .
#'
#' See the license file in
#'
#' @author Gürol Canbek,
#' @references
#' @keywords binary classification, machine learning, performance metrics, meta-metrics
#' @title MetaMetrics – Binary-Classification Performance-Metrics Benchmarking (Stage 2)
#' @date 25 February 2019
#' @version 1.1
#' @note version history
#' 1.1, 25 February 2019, Smoothness plot is added
#' 1.0, 15 May 2018, The first version
#' 0.1, December 2017, Draft version
#' @description R scripts for evaluating performance metrics from mathematical perspective
plotDescriptiveCriteria <- function(
metrics=dataFrameByNames(benchmark.metrics.names.group1),
metric_names=benchmark.metrics.names.group1,
cols=benchmark.metrics[benchmark.metrics.names.group1, c('Colors')],
mfrow=bestRowColumnLayout(length(benchmark.metrics.names.group1)))
{
par(mfrow=mfrow)
for (i in 1:length(metric_names)) {
plotMetricHist(
metric=metrics[[i]], metric_name=metric_names[i],
extras=c('add.normal'),
color_metric=cols[i],
color_element = 'black', color_note='black',
color_set.others=c('#00008F', '#000000', '#23FFDC',
'#ECFF13', '#FF4A00', '#800000'))
}
par(mfrow=c(1,1))
}
plotOuputSmothness <- function(
metrics=dataFrameByNames(benchmark.metrics.names.group1),
metric_names=benchmark.metrics.names.group1,
cols=benchmark.metrics[benchmark.metrics.names.group1, c('Colors')],
mfrow=bestRowColumnLayout(length(benchmark.metrics.names.group1)))
{
par(mfrow=mfrow)
for (i in 1:length(metric_names)) {
plot(
sort(metrics[[i]]),
xlab=NULL,
ylab=metric_names[i],
# pch=20, col=cols[i])
type='l', col=cols[i])
}
par(mfrow=c(1,1))
}