Find the best classifier using leave-one-out cross validation (svm) and out-of-bag error (random forests). Returns a list of classifier results
1 | classifier_accuracies(peaks, labels, training, min_peak_percentage)
|
peaks |
Boolean matrix of mass spectra rows with m/z columns, indicating if an m/z value corresponds to a peak. |
labels |
The correct classifications of the peaks. |
training |
The rows to actually use to train |
minpeaks |
How many "true" values must show up for a given m/z value for it to be considered a feature. |
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