Base class to handle the results of general Nonnegative Matrix Factorisation algorithms (NMF).
The function NMFfit is a factory method for NMFfit
objects, that should not need to be called by the user.
It is used internally by the functions nmf
and seed to instantiate the starting point of NMF
algorithms.
NMFfit(fit = nmfModel(), ..., rng = NULL)
an NMF model
extra argument used to initialise slots in the
instantiating NMFfit object.
RNG settings specification (typically a
suitable value for .Random.seed).
An object that inherits from class
NMF, and contains the fitted NMF
model.
NB: class NMF is a virtual class. The default
class for this slot is NMFstd, that implements the
standard NMF model.
A numeric vector that contains
the final residuals or the residuals track between the
target matrix and its NMF estimate(s). Default value is
numeric().
See method residuals for details on
accessor methods and main interface nmf for
details on how to compute NMF with residuals tracking.
a single character string that
contains the name of the algorithm used to fit the model.
Default value is ''.
a single character string that
contains the name of the seeding method used to seed the
algorithm that fitted the NMF model. Default value is
''. See nmf for more details.
an object that contains the RNG settings used
for the fit. Currently the settings are stored as an
integer vector, the value of .Random.seed
at the time the object is created. It is initialized by
the initialized method. See getRNG
for more details.
either a single "character" string
that contains the name of the built-in objective
function, or a function that measures the
residuals between the target matrix and its NMF estimate.
See objective and
deviance,NMF-method.
a list that contains the extra
parameters -- usually specific to the algorithm -- that
were used to fit the model.
object of class "proc_time" that
contains various measures of the time spent to fit the
model. See system.time
a list that contains the options
used to compute the object.
a list that contains extra
miscellaneous data for internal usage only. For example
it can be used to store extra parameters or temporary
data, without the need to explicitly extend the
NMFfit class. Currently built-in algorithms only
use this slot to store the number of iterations performed
to fit the object.
Data that need to be easily accessible by the end-user
should rather be set using the methods $<- that
sets elements in the list slot misc -- that
is inherited from class NMF.
stored call to the last nmf method
that generated the object.
signature(object = "NMFfit"):
Returns the name of the algorithm that fitted the NMF
model object.
signature(object = "NMFfit"):
Returns the basis matrix from an NMF model fitted with
function nmf.
It is a shortcut for .basis(fit(object), ...),
dispatching the call to the .basis method of the
actual NMF model.
signature(object = "NMFfit", value
= "matrix"): Sets the the basis matrix of an NMF model
fitted with function nmf.
It is a shortcut for .basis(fit(object)) <- value,
dispatching the call to the .basis<- method of the
actual NMF model. It is not meant to be used by the user,
except when developing NMF algorithms, to update the
basis matrix of the seed object before returning it.
signature(object = "NMFfit"): Returns
the the coefficient matrix from an NMF model fitted with
function nmf.
It is a shortcut for .coef(fit(object), ...),
dispatching the call to the .coef method of the
actual NMF model.
signature(object = "NMFfit", value =
"matrix"): Sets the the coefficient matrix of an NMF
model fitted with function nmf.
It is a shortcut for .coef(fit(object)) <- value,
dispatching the call to the .coef<- method of the
actual NMF model. It is not meant to be used by the user,
except when developing NMF algorithms, to update the
coefficient matrix in the seed object before returning
it.
signature(object = "NMFfit"):
Compare multiple NMF fits passed as arguments.
signature(object = "NMFfit"):
Returns the deviance of a fitted NMF model.
This method returns the final residual value if the
target matrix y is not supplied, or the
approximation error between the fitted NMF model stored
in object and y. In this case, the
computation is performed using the objective function
method if not missing, or the objective of the
algorithm that fitted the model (stored in slot
'distance').
See deviance,NMFfit-method for more
details.
signature(object = "NMFfit"): Returns
the NMF model object stored in slot 'fit'.
signature(object = "NMFfit", value =
"NMF"): Updates the NMF model object stored in slot
'fit' with a new value.
signature(object = "NMFfit"):
Computes and return the estimated target matrix from an
NMF model fitted with function nmf.
It is a shortcut for fitted(fit(object), ...),
dispatching the call to the fitted method of the
actual NMF model.
signature(object = "NMFfit"):
Method for single NMF fit objects, which returns the
indexes of fixed basis terms from the fitted model.
signature(object = "NMFfit"):
Method for single NMF fit objects, which returns the
indexes of fixed coefficient terms from the fitted model.
signature(object = "NMFfit"):
Method for multiple NMF fit objects, which returns the
indexes of fixed coefficient terms from the best fitted
model.
signature(object = "NMFfit"):
Returns the object its self, since there it is the result
of a single NMF run.
signature(object = "NMFfit"):
Returns the type of a fitted NMF model. It is a shortcut
for modelname(fit(object).
signature(object = "NMFfit"): Returns
the number of iteration performed to fit an NMF model,
typically with function nmf.
Currently this data is stored in slot 'extra', but
this might change in the future.
signature(object = "NMFfit", value =
"numeric"): Sets the number of iteration performed to
fit an NMF model.
This function is used internally by the function
nmf. It is not meant to be called by the
user, except when developing new NMF algorithms
implemented as single function, to set the number of
iterations performed by the algorithm on the seed, before
returning it (see
NMFStrategyFunction).
signature(x = "NMFfit", y =
"NMF"): Compares two NMF models when at least one comes
from a NMFfit object, i.e. an object returned by a single
run of nmf.
signature(x = "NMFfit", y =
"NMFfit"): Compares two fitted NMF models, i.e. objects
returned by single runs of nmf.
signature(object = "NMFfit"):
Creates an NMFfitX1 object from a single fit. This
is used in nmf when only the best fit is
kept in memory or on disk.
signature(object = "NMFfit"): This
method always returns 1, since an NMFfit object is
obtained from a single NMF run.
signature(object = "NMFfit"):
Returns the objective function associated with the
algorithm that computed the fitted NMF model
object, or the objective value with respect to a
given target matrix y if it is supplied.
signature(object = "NMFfit"):
Returns the offset from the fitted model.
signature(x = "NMFfit", y =
"missing"): Plots the residual track computed at regular
interval during the fit of the NMF model x.
signature(object = "NMFfit"):
Returns the residuals -- track -- between the target
matrix and the NMF fit object.
signature(object = "NMFfit"):
Returns the CPU time required to compute a single NMF
fit.
signature(object = "NMFfit"):
Identical to runtime, since their is a single fit.
signature(object = "NMFfit"):
Returns the name of the seeding method that generated the
starting point for the NMF algorithm that fitted the NMF
model object.
signature(object = "NMFfit"): Show
method for objects of class NMFfit
signature(object = "NMFfit"):
Computes summary measures for a single fit from
nmf.
This method adds the following measures to the measures
computed by the method summary,NMF:
See summary,NMFfit-method for more details.
It provides a general structure and generic functions to
manage the results of NMF algorithms. It contains a slot
with the fitted NMF model (see slot fit) as well
as data about the methods and parameters used to compute
the factorization.
The purpose of this class is to handle in a generic way
the results of NMF algorithms. Its slot fit
contains the fitted NMF model as an object of class
NMF.
Other slots contains data about how the factorization has been computed, such as the algorithm and seeding method, the computation time, the final residuals, etc...
Class NMFfit acts as a wrapper class for its slot
fit. It inherits from interface class
NMF defined for generic NMF models.
Therefore, all the methods defined by this interface can
be called directly on objects of class NMFfit. The
calls are simply dispatched on slot fit, i.e. the
results are the same as if calling the methods directly
on slot fit.
# roxygen generated flag
options(R_CHECK_RUNNING_EXAMPLES_=TRUE)
# run default NMF algorithm on a random matrix
n <- 50; r <- 3; p <- 20
V <- rmatrix(n, p)
res <- nmf(V, r)
# result class is NMFfit
class(res)
isNMFfit(res)
# show result
res
# compute summary measures
summary(res, target=V)
Run the code above in your browser using DataLab