fit {NMF} | R Documentation

## Extracting Fitted Models

### Description

The functions `fit` and `minfit` are S4 genetics that extract the best model object and the best fit object respectively, from a collection of models or from a wrapper object.

`fit<-` sets the fitted model in a fit object. It is meant to be called only when developing new NMF algorithms, e.g. to update the value of the model stored in the starting point.

### Usage

      fit(object, ...)

      fit(object)<-value

      minfit(object, ...)

### Arguments

`object` | an object fitted by some algorithm, e.g. as returned by the function `nmf`.
`value` | replacement value
`...` | extra arguments to allow extension

### Details

A fit object differs from a model object in that it contains data about the fit, such as the initial RNG settings, the CPU time used, etc..., while a model object only contains the actual modelling data such as regression coefficients, loadings, etc...

That best model is generally defined as the one that achieves the maximum/minimum some quantitative measure, amongst all models in a collection.

In the case of NMF models, the best model is the one that achieves the best approximation error, according to the objective function associated with the algorithm that performed the fit(s).

### Methods

fit

  `signature(object = "NMFfit")`: Returns the NMF model object stored in slot `'fit'`.

fit

  `signature(object = "NMFfitX")`: Returns the model object that achieves the lowest residual approximation error across all the runs.

  It is a pure virtual method defined to ensure `fit` is defined for sub-classes of `NMFfitX`, which throws an error if called.

fit

  `signature(object = "NMFfitX1")`: Returns the model object associated with the best fit, amongst all the runs performed when fitting `object`.

  Since `NMFfitX1` objects only hold the best fit, this method simply returns the NMF model fitted by `object` – that is stored in slot ‘fit’.

fit

  `signature(object = "NMFfitXn")`: Returns the best NMF fit object amongst all the fits stored in `object`, i.e. the fit that achieves the lowest estimation residuals.

fit<-

  `signature(object = "NMFfit", value = "NMF")`: Updates the NMF model object stored in slot `'fit'` with a new value.

minfit

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

minfit

  `signature(object = "NMFfitX")`: Returns the fit object that achieves the lowest residual approximation error across all the runs.

  It is a pure virtual method defined to ensure `minfit` is defined for sub-classes of `NMFfitX`, which throws an error if called.

minfit

  `signature(object = "NMFfitX1")`: Returns the fit object associated with the best fit, amongst all the runs performed when fitting `object`.

  Since `NMFfitX1` objects only hold the best fit, this method simply returns `object` coerced into an `NMFfit` object.

minfit

  `signature(object = "NMFfitXn")`: Returns the best NMF model in the list, i.e. the run that achieved the lower estimation residuals.

  The model is selected based on its `deviance` value.

[Package NMF version 0.20.6 Index]