random_forest: Predict scores using a random forest.

In johrpan/geposan: Gene Position Analysis

Predict scores using a random forest.

Description

Predict scores using a random forest.

Usage

random_forest(
  id = "rforest",
  name = "Random forest",
  description = "Assessment by random forest",
  seed = 180199,
  n_models = NULL,
  control_ratio = 0.75
)

Arguments

id	Unique ID for the method and its results.
name	Human readable name for the method.
description	Method description.
seed	The seed will be used to make the results reproducible.
n_models	This number specifies how many sets of training data should be created. For each set, there will be a model trained on the remaining training data and validated using this set. For non-training genes, the final score will be the mean of the result of applying the different models. There should be at least two training sets. The analysis will only work, if there is at least one reference gene per training set. By default, one model per reference gene will be used.
control_ratio	The proportion of random control genes that is included in the training data sets in addition to the reference genes. This should be a numeric value between 0.0 and 1.0.

Value

An object of class geposan_method.

johrpan/geposan documentation built on Feb. 28, 2025, 3:48 a.m.