Description Usage Arguments Details Slots Methods Examples
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.
1 
fit 
an NMF model 
... 
extra argument used to initialise slots in the instantiating

rng 
RNG settings specification (typically a suitable value for

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
.
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 builtin objective function, or a function
that measures the residuals between the target matrix and its NMF estimate.
See objective
and deviance,NMFmethod
.
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 builtin 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 enduser 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,NMFfitmethod
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,NMFfitmethod
for more details.
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