accuracy_hpc: Test the robustness of clusters

In PatZeis/AssessMe: A cluster assessment tool for preprocessing and clustering optimization

Test the robustness of clusters

Description

accuracy function to be executed on a high performing computing cluster system.

Usage

accuracy_hpc(generate, crossvali = iterat, ntree = 200, loreg = F)

Arguments

generate	output of generate_input_accuracy_hpc function.
crossvali	numeric index to iterate through indixes of n-fold sampled cells for training data.
ntree	number of trees to grow for random forest based reclassification.
loreg	logical. If T, perform n-fold crossvalidation based on multionomial logistic regression. Default = F.

Examples

give_accuracy <- accuracy(generate = tes_generate, crossvali = iterat, ntree = 100)

PatZeis/AssessMe documentation built on Nov. 19, 2022, 6:03 a.m.