phenorm_longit_simpl: phenorm_longit_simpl

In PheVis: Automatic Phenotyping of Electronic Health Record at Visit Resolution

phenorm_longit_simpl

Description

'PheNorm' like function adapted to longitudinal data.

Usage

phenorm_longit_simpl(
  df,
  var_surrogate,
  surrogates_quali,
  id_rnd,
  rf = FALSE,
  ntree = 100,
  bool_weight = FALSE,
  p.noise = 0.3,
  bool_SAFE = TRUE,
  size = 10^5
)

Arguments

df	dataframe
var_surrogate	variables used for building the surrogates
surrogates_quali	numeric vector of the qualitative surrogate
id_rnd	ID for random effect
rf	should pseudo-labellisation with random forest be used (default is FALSE)
ntree	number of tree for randomforest (default is 100)
bool_weight	should the sampling probability balance the number of positive and negative extrema.
p.noise	percentage of noise introduced during the noising step
bool_SAFE	A boolean. If TRUE, SAFE selection is done, else it is not (default is TRUE)
size	minimum size of sampling

Value

A list with the logistic model, the random forest model, the variables selected for prediction and the predictions

PheVis documentation built on Oct. 20, 2023, 9:08 a.m.