plot.perf: Plot for model performance for PSLDA analyses

plot.perfR 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.


mixOmicsTeam/mixOmics documentation built on Nov. 4, 2024, 8:56 a.m.