MisclassificationEstimate: RNA-Seq classifier evaluation to assesse the performance of...

In elqumsan/RNAseqMVA: Application of Multivariate Analysis methods to RNA-seq Data

Description

this script to evaluate and assesse the performance of the RNA-Seq classifier by Random sampling (random partitioning) estimation of the misclassification rate.

Usage

MisclassificationEstimate(
  dataset,
  iteration,
  classifier,
  permute = FALSE,
  stratifiedPermutation = FALSE
)

Arguments

dataset	an object of class DataTableWithTrainTestSets
iteration	current iteration number (the MisclassificationEstimate function is typically called iteratively) and it called number of resampling.
classifier	is a type of the classifier.
permute=FALSE	if TRUE, permute the calss labels to measure misclassifciation rate without relevant training

Value

• dataset = it is data table one row for the individual (sample) and one culomn for the feature (gene).

• classifier = what is the tested classifier, KNN, RF, SVM and LDA.

• iteration = nomber of resampling.

• testPredictedClasses = these are the test classes which are predicted from classifier.

• trainPredictedClasses = these are the train classes whci are predicated from classifier.

Author(s)

Mustafa ABUELQUMSAN and Jacques van Helden

elqumsan/RNAseqMVA documentation built on March 10, 2021, 8:10 a.m.