MessinaResult-class: The MessinaResult class
In messina: Single-gene classifiers and outlier-resistant detection of differential expression for two-group and survival problems
Description
Slots
Author(s)
See Also
Description
A class to store the results of a messina or messinaSurv
analysis.
Slots
problem_typeA character string naming the variant of the messina
algorithm used, either "classification" for the classification case
(fit using the function messina), or "survival" for the outcome case
(fit using the function messinaSurv).
parametersAn object of class MessinaParameters, containing
input data and parameters for the algorithm.
perf_estimatesA data frame of summary performance estimates
(evaluated on many out-of-bag sample draws), with one row per feature
in the data matrix supplied to the fit functions (either messina or
messinaSurv). For a messina fit, this contains 10 columns:
Mean TPR, Mean FPR, Mean TNR, Mean FNR, Variance of TPR, Variance
of FPR, Variance of TNR, Variance of FNR, Mean sensitivity, Mean
specificity. For a messinaSurv fit, this contains a single column,
of the mean objective value for that row's feature.
fitsAn object of class MessinaFits, containing details of the
fits for each feature.
Author(s)
Mark Pinese m.pinese@garvan.org.au
See Also
messina documentation built on Nov. 8, 2020, 7:47 p.m.
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Description Slots Author(s) See Also
Description
A class to store the results of a messina or messinaSurv analysis.
Slots
problem_typeA character string naming the variant of the messina algorithm used, either "classification" for the classification case (fit using the function messina), or "survival" for the outcome case (fit using the function messinaSurv).
parametersAn object of class MessinaParameters, containing input data and parameters for the algorithm.
perf_estimatesA data frame of summary performance estimates (evaluated on many out-of-bag sample draws), with one row per feature in the data matrix supplied to the fit functions (either messina or messinaSurv). For a messina fit, this contains 10 columns: Mean TPR, Mean FPR, Mean TNR, Mean FNR, Variance of TPR, Variance of FPR, Variance of TNR, Variance of FNR, Mean sensitivity, Mean specificity. For a messinaSurv fit, this contains a single column, of the mean objective value for that row's feature.
fitsAn object of class MessinaFits, containing details of the fits for each feature.
Author(s)
Mark Pinese m.pinese@garvan.org.au
See Also
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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