neural: Refactor and increase gene requirement

This commit is contained in:
Elias Projahn 2022-05-26 19:50:23 +02:00
parent c04b6337e9
commit 49981300fb
2 changed files with 168 additions and 140 deletions

View file

@ -4,7 +4,12 @@
\alias{neural}
\title{Find genes by training and applying a neural network.}
\usage{
neural(seed = 180199, n_models = 5)
neural(
seed = 180199,
n_models = 5,
gene_requirement = 0.5,
control_ratio = 0.5
)
}
\arguments{
\item{seed}{The seed will be used to make the results reproducible.}
@ -15,6 +20,13 @@ 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.}
\item{gene_requirement}{Minimum proportion of genes from the preset that a
species has to have in order to be included in the models.}
\item{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 \code{geposan_method}.