assessModelQuality {parafac4microbiome} | R Documentation |
Create randomly initialized models to determine the correct number of components by assessing model quality metrics.
assessModelQuality(
X,
minNumComponents = 1,
maxNumComponents = 5,
numRepetitions = 100,
method = "als",
ctol = 1e-06,
maxit = 2500,
max_fn = 10000,
rel_tol = 1e-08,
abs_tol = 1e-08,
grad_tol = 1e-08,
numCores = 1
)
X |
Input data |
minNumComponents |
Minimum number of components (default 1). |
maxNumComponents |
Maximum number of components (default 5). |
numRepetitions |
Number of randomly initialized models to create (default 100). |
method |
Use ALS algorithm ("als", default) or use all-at-once optimization ("opt"). The all-at-once optimization is based on a nonlinear conjugate gradient method with Hestenes-Stiefel updates and the More-Thuente line search algorithm. |
ctol |
Change in SSQ needed for model to be converged (default 1e-6). |
maxit |
Maximum number of iterations (default 2500). |
max_fn |
Maximum number of function evaluations allowed without convergence in the OPT case (default 10000). |
rel_tol |
Relative change in loss tolerated to call the algorithm converged in the OPT case (default 1e-8). |
abs_tol |
Absolute loss tolerated to call the algorithm converged in the OPT case (default 1e-8). |
grad_tol |
Tolerance on the two-norm of the gradient divided over the number of elements in the gradient in the OPT case (default 1e-8). |
numCores |
Number of cores to use. If set larger than 1, it will run the job in parallel (default 1) |
A list object of the following:
plots: Plots of all assessed metrics and an overview plot showing a summary of all of them.
metrics: metrics of every created model (number of iterations, sum of squared errors, CORCONDIA score and variance explained).
models: all created models.
X = Fujita2023$data
# Run assessModelQuality with less strict convergence parameters as example
assessment = assessModelQuality(X,
minNumComponents=1,
maxNumComponents=3,
numRepetitions=5,
ctol=1e-4,
maxit=250)
assessment$plots$overview