R: plot_R_NX

plot_R_NX {dimRed} | R Documentation

## plot_R_NX

### Description

Plot the R_NX curve for different embeddings. Takes a list of `dimRedResult` objects as input. Also the Area under the curve values are computed for a weighted K (see AUC_lnK_R_NX for details) and appear in the legend.

### Usage

    plot_R_NX(x, ndim = NA, weight = "inv")

### Arguments

`x` | a list of `dimRedResult` objects. The names of the list will appear in the legend with the AUC_lnK value.
`ndim` | the number of dimensions, if `NA` the original number of embedding dimensions is used, can be a vector giving the embedding dimensionality for each single list element of `x`.
`weight` | the weight function used for K when calculating the AUC, one of `c("inv", "log", "log10")`

### Value

A ggplot object, the design can be changed by appending `theme(...)`

### See Also

Other Quality scores for dimensionality reduction: `AUC_lnK_R_NX,dimRedResult-method`, `LCMC,dimRedResult-method`, `Q_NX,dimRedResult-method`, `Q_global,dimRedResult-method`, `Q_local,dimRedResult-method`, `R_NX,dimRedResult-method`, `cophenetic_correlation,dimRedResult-method`, `distance_correlation,dimRedResult-method`, `mean_R_NX,dimRedResult-method`, `quality,dimRedResult-method`, `reconstruction_error,dimRedResult-method`, `reconstruction_rmse,dimRedResult-method`, `total_correlation,dimRedResult-method`

### Examples

    ## define which methods to apply
    embed_methods <- c("Isomap", "PCA")
    ## load test data set
    data_set <- loadDataSet("3D S Curve", n = 200)
    ## apply dimensionality reduction
    data_emb <- lapply(embed_methods, function(x) embed(data_set, x))
    names(data_emb) <- embed_methods
    ## plot the R_NX curves:
    plot_R_NX(data_emb) +
        ggplot2::theme(legend.title = ggplot2::element_blank(),
                       legend.position = c(0.5, 0.1),
                       legend.justification = c(0.5, 0.1))

[Package dimRed version 0.2.4 Index]