ss_classify_h2o: Classify using h2o classification algorithms

In Vitek-Lab/MSstatsSampleSize: Simulation tool for optimal design of high-dimensional MS-based proteomics experiment

Description

This function enables the shiny application to apply various algorithms as defined by the user

Usage

ss_classify_h2o(
  n_samp,
  sim_data,
  classifier,
  stopping_metric = "AUTO",
  seed = -1,
  nfolds = 0,
  fold_assignment = "AUTO",
  iters = 200,
  alpha = 0,
  family,
  solver,
  link,
  min_sdev,
  laplace,
  eps,
  session = NULL
)

Arguments

n_samp	A comma separated chracter vector with number of sample sizes
sim_data	A list object containing simulated data
classifier	Classifier to use as selected by the user can use one of the following 'Logistic Regression', 'Random Forest', 'Support Vector Machine', 'Naive Bayes', 'Neural Network'
stopping_metric
session

Vitek-Lab/MSstatsSampleSize documentation built on Aug. 28, 2020, 10:39 a.m.