plot.perf {mixOmics} | R Documentation

## Plot for model performance for PSLDA analyses

### Description

Function to plot classification performance for supervised methods, as a function of the number of components.

### Usage

    ## S3 method for class 'perf.plsda.mthd'
    plot(
      x,
      dist = c("all", "max.dist", "centroids.dist", "mahalanobis.dist"),
      measure = c("all", "overall", "BER"),
      col,
      xlab = NULL,
      ylab = NULL,
      overlay = c("all", "measure", "dist"),
      legend.position = c("vertical", "horizontal"),
      sd = TRUE,
      ...
    )

    ## S3 method for class 'perf.splsda.mthd'
    plot(
      x,
      dist = c("all", "max.dist", "centroids.dist", "mahalanobis.dist"),
      measure = c("all", "overall", "BER"),
      col,
      xlab = NULL,
      ylab = NULL,
      overlay = c("all", "measure", "dist"),
      legend.position = c("vertical", "horizontal"),
      sd = TRUE,
      ...
    )

    ## S3 method for class 'perf.mint.plsda.mthd'
    plot(
      x,
      dist = c("all", "max.dist", "centroids.dist", "mahalanobis.dist"),
      measure = c("all", "overall", "BER"),
      col,
      xlab = NULL,
      ylab = NULL,
      study = "global",
      overlay = c("all", "measure", "dist"),
      legend.position = c("vertical", "horizontal"),
      ...
    )

    ## S3 method for class 'perf.mint.splsda.mthd'
    plot(
      x,
      dist = c("all", "max.dist", "centroids.dist", "mahalanobis.dist"),
      measure = c("all", "overall", "BER"),
      col,
      xlab = NULL,
      ylab = NULL,
      study = "global",
      overlay = c("all", "measure", "dist"),
      legend.position = c("vertical", "horizontal"),
      ...
    )

    ## S3 method for class 'perf.sgccda.mthd'
    plot(
      x,
      dist = c("all", "max.dist", "centroids.dist", "mahalanobis.dist"),
      measure = c("all", "overall", "BER"),
      col,
      weighted = TRUE,
      xlab = NULL,
      ylab = NULL,
      overlay = c("all", "measure", "dist"),
      legend.position = c("vertical", "horizontal"),
      sd = TRUE,
      ...
    )

### Arguments

`x` | an `perf.plsda` object.
`dist` | prediction method applied in `perf` for `plsda` or `splsda`. See `perf`.
`measure` | Two misclassification measure are available: overall misclassification error `overall` or the Balanced Error Rate `BER`
`col` | character (or symbol) colour to be used, possibly vector. One color per distance `dist`.
`xlab, ylab` | titles for x and y axes. Typically character strings, but can be expressions (e.g., `expression(R^2)`).
`overlay` | parameter to overlay graphs; if 'all', only one graph is shown with all outputs; if 'measure', a graph is shown per distance; if 'dist', a graph is shown per measure.
`legend.position` | position of the legend, one of "vertical" (only one column) or "horizontal" (two columns).
`sd` | If 'nrepeat' was used in the call to 'perf', error bar shows the standard deviation if sd=TRUE. For mint objects sd is set to FALSE as the number of repeats is 1.
`...` | Not used.
`study` | Indicates which study-specific outputs to plot. A character vector containing some levels of `object$study`, "all.partial" to plot all studies or "global" is expected. Default to "global".
`weighted` | plot either the performance of the Majority vote or the Weighted vote.

### Details

More details about the prediction distances in `?predict` and the supplemental material of the mixOmics article (Rohart et al. 2017). See ?perf for examples.

### Value

none

### Author(s)

Ignacio González, Florian Rohart, Francois Bartolo, Kim-Anh Lê Cao, Al J Abadi

### References

Rohart F, Gautier B, Singh A, Lê Cao K-A. mixOmics: an R package for 'omics feature selection and multiple data integration. PLoS Comput Biol 13(11): e1005752

### See Also

`pls`, `spls`, `plsda`, `splsda`, `perf`.

[Package mixOmics version 6.14.1 Index]