plot.perf {mixOmics} | R Documentation

## Plot for model performance

### Description

Function to plot performance criteria, such as MSEP, RMSEP, R^2, Q^2 for s/PLS methods, and classification performance for supervised methods, as a function of the number of components.

### Usage

    ## S3 method for class 'perf.spls.mthd'
    plot(x,
    criterion = "MSEP",
    xlab = "number of components",
    ylab = NULL,
    LimQ2 = 0.0975,
    LimQ2.col = "darkgrey",
    cTicks = NULL,
    layout = NULL,
    ...)

    ## 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.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` object.
`criterion` | character string. What type of validation criterion to plot for `pls` or `spls`. One of `"MSEP"`, `"RMSEP"`, `"R2"` or `"Q2"`. See `perf`.
`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) color to be used, possibly vector. One color per distance `dist`.
`weighted` | plot either the performance of the Majority vote or the Weighted vote.
`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".
`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).
`xlab, ylab` | titles for x and y axes. Typically character strings, but can be expressions (e.g., `expression(R^2)`).
`LimQ2` | numeric value. Signification limit for the components in the model. Default is `LimQ2 = 0.0975`.
`LimQ2.col` | character string specifying the color for the `LimQ2` line to be plotted. If `"none"` the line will not be plotted.
`cTicks` | integer vector. Axis tickmark locations for the used number of components. Default is `1:ncomp` (see `perf`).
`layout` | numeric vector of length two giving the number of rows and columns in a multi panel display. If not specified, `plot.perf` tries to be intelligent.
`sd` | If 'nrepeat' was used in the call to 'perf', error bar shows the standard deviation if sd=TRUE
`...` | Further arguments sent to `xyplot` function.

### Details

`plot.perf` creates one plot for each response variable in the model, laid out in a multi panel display. It uses `xyplot` for performing the actual plotting.

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

### Value

none

### Author(s)

Ignacio González, Florian Rohart, Francois Bartolo, Kim-Anh Lê Cao.

### 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`.

### Examples

    require(lattice)

    ## validation for objects of class 'pls' or 'spls'

    data(liver.toxicity)
    X <- liver.toxicity$gene
    Y <- liver.toxicity$clinic

    liver.pls <- pls(X, Y, ncomp = 3)
    liver.perf <- perf(liver.pls, validation = "Mfold")

    plot(liver.perf, criterion = "R2", layout = c(2, 2))

    ## Not run:
    ## validation for objects of class 'plsda' or 'splsda'

    data(breast.tumors)
    X <- breast.tumors$gene.exp
    # Y will be transformed as a factor in the function,
    # but we set it as a factor to set up the colors.
    Y <- as.factor(breast.tumors$sample$treatment)

    res <- splsda(X, Y, ncomp = 2, keepX = c(25, 25))
    breast.perf <- perf(res, nrepeat = 5)

    plot(breast.perf)
    plot(breast.perf, col=1:3)
    plot(breast.perf, col=1:3, sd=FALSE)

    ## End(Not run)

[Package mixOmics version 6.10.9 Index]