Training an ensemble classifier for cell type prediction.

Training an ensemble classifier for cell type prediction.

FitEnsemblMultiClassif(
  feature.mat,
  cell.types,
  do.norm = "L2",
  mlr3.model = "classif.svm",
  batch.size = 5000,
  n.models = 100,
  balance.cell.type = TRUE,
  cores = -1
)

Arguments

feature.mat

A signature score matrix, rows are cells, columns are features.

cell.types

A data.frame recording cell types at different granularity.

do.norm

Whether normalize the feature matrix. L1, L2, NULL. Default: 'L2'

mlr3.model

classif.svm, classif.xgboost, classif.randomForest. Default: classif.svm

batch.size

The number of cells for each model. Default: 5000

n.models

The number of SVM model. Default: 100

balance.cell.type

A boolen determines whether performing balance sampling. Default: True

cores

The number of CPU for training. Default: -1, use all available threads.

Value

a list of trained learners.