2019-feature-selection: Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"

#' @import future
#' @import data.table
#' @import ggplot2
#' @import magrittr
#' @import drake
#' @import ggpubr
#' @import R.utils
#' @import mlrMBO
"_PACKAGE"

pat-s/2019-feature-selection documentation built on Dec. 24, 2021, 8:40 a.m.

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pat-s/2019-feature-selection
Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"

R/FeatureSelection.R
In pat-s/2019-feature-selection: Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"

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pat-s/2019-feature-selection Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"

R/FeatureSelection.R In pat-s/2019-feature-selection: Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"

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We want your feedback!

pat-s/2019-feature-selection
Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"

R/FeatureSelection.R
In pat-s/2019-feature-selection: Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"