adjust_frm: Adjust an existing FastRet model for use with a new column

In FastRet: Retention Time Prediction in Liquid Chromatography

Adjust an existing FastRet model for use with a new column

Description

The goal of this function is to train a model that predicts RT_ADJ (retention time measured on a new, adjusted column) from RT (retention time measured on the original column) and to attach this "adjustmodel" to an existing FastRet model.

Usage

adjust_frm(
  frm = train_frm(),
  new_data = read_rpadj_xlsx(),
  predictors = 1:6,
  nfolds = 5,
  verbose = 1
)

Arguments

frm	An object of class frm as returned by train_frm().
new_data	Dataframe with columns "RT", "NAME", "SMILES" and optionally a set of chemical descriptors.
predictors	Numeric vector specifying which predictors to include in the model in addition to RT. Available options are: 1=RT, 2=RT^2, 3=RT^3, 4=log(RT), 5=exp(RT), 6=sqrt(RT).
nfolds	An integer representing the number of folds for cross validation.
verbose	A logical value indicating whether to print progress messages.

Value

An object of class frm, which is a list with the following elements:

• model: A list containing details about the original model.

• df: The data frame used for training the model.

• cv: A list containing the cross validation results.

• seed: The seed used for random number generation.

• version: The version of the FastRet package used to train the model.

• adj: A list containing details about the adjusted model.

Examples

frm <- read_rp_lasso_model_rds()
new_data <- read_rpadj_xlsx()
frmAdjusted <- adjust_frm(frm, new_data, verbose = 0)

FastRet documentation built on June 25, 2024, 5:07 p.m.