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)

- fit
- an NMF model
- ...
- extra argument used to initialise slots in the
instantiating
`NMFfit`

object. - rng
- RNG settings specification (typically a
suitable value for
`.Random.seed`

).

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-class`

.

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-class`

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`

.

- fitAn object that inherits from class
`NMF-class`

, 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. - residualsA
`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. - methoda single
`character`

string that contains the name of the algorithm used to fit the model. Default value is`''`

. - seeda 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. - rngan 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. - distanceeither 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`

. - parametersa
`list`

that contains the extra parameters -- usually specific to the algorithm -- that were used to fit the model. - runtimeobject of class
`"proc_time"`

that contains various measures of the time spent to fit the model. See`system.time`

- optionsa
`list`

that contains the options used to compute the object. - extraa
`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-class`

. - callstored call to the last
`nmf`

method that generated the object.

- algorithm
`signature(object = "NMFfit")`

: Returns the name of the algorithm that fitted the NMF model`object`

. - .basis
`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. - .basis<-
`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. - .coef
`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. - .coef<-
`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. - compare
`signature(object = "NMFfit")`

: Compare multiple NMF fits passed as arguments. - deviance
`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. - fit
`signature(object = "NMFfit")`

: Returns the NMF model object stored in slot`'fit'`

. - fit<-
`signature(object = "NMFfit", value = "NMF")`

: Updates the NMF model object stored in slot`'fit'`

with a new value. - fitted
`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. - ibterms
`signature(object = "NMFfit")`

: Method for single NMF fit objects, which returns the indexes of fixed basis terms from the fitted model. - icterms
`signature(object = "NMFfit")`

: Method for single NMF fit objects, which returns the indexes of fixed coefficient terms from the fitted model. - icterms
`signature(object = "NMFfit")`

: Method for multiple NMF fit objects, which returns the indexes of fixed coefficient terms from the best fitted model. - minfit
`signature(object = "NMFfit")`

: Returns the object its self, since there it is the result of a single NMF run. - modelname
`signature(object = "NMFfit")`

: Returns the type of a fitted NMF model. It is a shortcut for`modelname(fit(object)`

. - niter
`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. - niter<-
`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-class`

). - nmf.equal
`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`

. - nmf.equal
`signature(x = "NMFfit", y = "NMFfit")`

: Compares two fitted NMF models, i.e. objects returned by single runs of`nmf`

. - NMFfitX
`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. - nrun
`signature(object = "NMFfit")`

: This method always returns 1, since an`NMFfit`

object is obtained from a single NMF run. - objective
`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. - offset
`signature(object = "NMFfit")`

: Returns the offset from the fitted model. - plot
`signature(x = "NMFfit", y = "missing")`

: Plots the residual track computed at regular interval during the fit of the NMF model`x`

. - residuals
`signature(object = "NMFfit")`

: Returns the residuals -- track -- between the target matrix and the NMF fit`object`

. - runtime
`signature(object = "NMFfit")`

: Returns the CPU time required to compute a single NMF fit. - runtime.all
`signature(object = "NMFfit")`

: Identical to`runtime`

, since their is a single fit. - seeding
`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`

. - show
`signature(object = "NMFfit")`

: Show method for objects of class`NMFfit`

- summary
`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.

```
# 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)
```

```
## [1] "NMFfit"
## attr(,"package")
## [1] "NMF"
```

```
isNMFfit(res)
```

```
## [1] TRUE
```

```
# show result
res
```

```
## <Object of class: NMFfit>
## # Model:
## <Object of class:NMFstd>
## features: 50
## basis/rank: 3
## samples: 20
## # Details:
## algorithm: brunet
## seed: random
## RNG: 403L, 360L, ..., -1328735503L [8b3565035d1b766cf202020052da8274]
## distance metric: 'KL'
## residuals: 71.6
## Iterations: 580
## Timing:
## user system elapsed
## 0.168 0.000 0.166
```

```
# compute summary measures
summary(res, target=V)
```

```
## Length Class Mode
## 1 NMFfit S4
```

```
```