baseModel: Prediction by Machine Learning

In BioM2: Biologically Explainable Machine Learning Framework

Prediction by Machine Learning

Description

Prediction by Machine Learning with different learners ( From 'mlr3' )

Usage

baseModel(
  trainData,
  testData,
  predMode = "probability",
  classifier,
  paramlist = NULL,
  inner_folds = 10,
  seed = 10
)

Arguments

trainData	The input training dataset. The first column is the label or the output. For binary classes, 0 and 1 are used to indicate the class member.
testData	The input test dataset. The first column is the label or the output. For binary classes, 0 and 1 are used to indicate the class member.
predMode	The prediction mode.Currently only supports 'probability' for binary classification tasks.
classifier	Learners in mlr3
paramlist	Learner parameters search spaces
inner_folds	k-fold cross validation ( Only supported when testData = NULL )
seed	Cross-Validation seed

Value

The predicted output for the test data.

Author(s)

Shunjie Zhang

Examples

library(mlr3verse)
library(caret)
library(BioM2)
data=MethylData_Test
set.seed(1)
part=unlist(createDataPartition(data$label,p=0.8))#Split data
predict=baseModel(trainData=data[part,1:10],
                 testData=data[-part,1:10],
                 classifier = 'svm')#Use 10 features to make predictions,Learner uses svm

BioM2 documentation built on Aug. 8, 2025, 6:35 p.m.