plot_R_NX
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.
plot_R_NX(x, ndim = NA, weight = "inv")
x |
a list of |
ndim |
the number of dimensions, if |
weight |
the weight function used for K when calculating the AUC, one of
|
A ggplot object, the design can be changed by appending
theme(...)
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
## 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))
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