svm_false_positive_classification: svm_false_positive_classification

In alextkalinka/delboy: Differential-representation analysis by Elastic-net Logistic regression with BinOmial-thinning validitY tests

Description

Utilises an SVM to learn the decision boundary between false and true positives for validation data.

Usage

svm_false_positive_classification(
  data,
  use_fn = FALSE,
  grid_fc_dens = 600,
  grid_ex_dens = 800
)

Arguments

data	A data frame as produced by delboy::make_delboy_hit_comparison_table.
use_fn	Logical indicating whether false negatives should be used in conjunction with any false positives for the decision boundary. Defaults to FALSE.
grid_fc_dens	An integer giving the density of grid sampling for the decision boundary on the fold change axis. Defaults to 600.
grid_ex_dens	An integer giving the density of grid sampling for the decision boundary on the expression axis. Defaults to 800.

Value

A list containing the SVM fit, a data frame containing predicted false positive status, and a data frame produced by expand.grid.

alextkalinka/delboy documentation built on Feb. 2, 2022, 4:19 p.m.