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.

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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.

directlabels documentation built on May 31, 2017, 4:42 a.m.

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