Method reconstruction_error
Calculate the error using only the first n dimensions of the embedded
data. error_fun can either be one of c("rmse", "mae") to
calculate the root mean square error or the mean absolute error respectively,
or a function that takes to equally sized vectors as input and returns a
single number as output.
## S4 method for signature 'dimRedResult' reconstruction_error(object, n = seq_len(ndims(object)), error_fun = "rmse")
object |
of class dimRedResult |
n |
a positive integer or vector of integers |
error_fun |
a function or string indicating an error function, if indication a function it must take to matrices of the same size and return a scalar. |
a vector of number with the same length as n with the
Guido Kraemer
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,
plot_R_NX,
quality,dimRedResult-method,
reconstruction_rmse,dimRedResult-method,
total_correlation,dimRedResult-method
## Not run:
ir <- loadDataSet("Iris")
ir.drr <- embed(ir, "DRR", ndim = ndims(ir))
ir.pca <- embed(ir, "PCA", ndim = ndims(ir))
rmse <- data.frame(
rmse_drr = reconstruction_error(ir.drr),
rmse_pca = reconstruction_error(ir.pca)
)
matplot(rmse, type = "l")
plot(ir)
plot(ir.drr)
plot(ir.pca)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.