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# title : Machine learning exercise for Sentinel-2 data
# purpose : Implementing a machine learning workflow in R
# author : Abdulhakim M. Abdi (Twitter: @HakimAbdi / www.hakimabdi.com)
# input : A multi-temporal raster stack of Sentinel-2 data comprising scenes from four dates
# output : One classified land cover map from each of three machine learning algorithms
# Note 1 : This brief tutorial assumes that you are already well-grounded in R concepts and are
# : familiar with image classification procedure and terminology
# Reference : Please cite Abdi (2020): "Land cover and land use classification performance of machine learning
# : algorithms in a boreal landscape using Sentinel-2 data" in GIScience & Remote Sensing if you find this