False positive rates from several 1-SVM models

Description

Support Vector Machine density estimation (1-SVM) was applied to a set of negative control samples, and then used to test on a positive control.

Usage

1

Format

A data frame with 378 observations on the following 5 variables.

replicate

a factor with levels 1 2 3, the experimental replicate. We fit 1-SVM models to each replicate separately.

rate

a numeric vector, the percent of observations that were outside the trained model.

data

a factor with levels KIF11 test train, which set of observations did we measure. test and train are each 50% random splits of the negative controls in the experiment, and KIF11 is the positive control in the experiment.

gamma

a numeric vector, the tuning parameter of the radial basis function kernel.

nu

a numeric vector, the regularization parameter of the 1-SVM.

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