Input_training: Train XGBoost model to predict cell type

In MethScope: Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent Pattern Encoding

Train XGBoost model to predict cell type

Description

Train XGBoost model to predict cell type

Usage

Input_training(
  summary_results,
  cell_type_label,
  number_patterns = 1000,
  cross_validation = FALSE,
  xgb_parameters = list()
)

Arguments

summary_results	a wide cell by pattern matrix generated from GenerateInput function
cell_type_label	a vector of the corresponding cell type label for each row of the summary results
number_patterns	a numeric value to indicate number of patterns to be used (Default: 1000)
cross_validation	a boolean varaible whether to perform cross_validation to obtain the best hyper parameters for the model
xgb_parameters	an optional list for xgb model parameters provided by the user

Value

the xgb model trained

MethScope documentation built on Feb. 27, 2026, 1:08 a.m.