# Weka_classifiers_functions

From RWeka v0.1-0
by Kurt Hornik

##### R/Weka Classifier Functions

R interfaces to Weka regression and classification function learners.

- Keywords
- models, regression, classif

##### Usage

```
LinearRegression(formula, data, subset, na.action, control = NULL)
Logistic(formula, data, subset, na.action, control = NULL)
```

##### Arguments

- formula
- a symbolic description of the model to be fit.
- data
- an optional data frame containing the variables in the model.
- subset
- an optional vector specifying a subset of observations to be used in the fitting process.
- na.action
- a function which indicates what should happen when
the data contain
`NA`

s. - control
- a character vector with control options, or
`NULL`

(default). Available options can be obtained on-line using the Weka Option Wizard`WOW`

, or the Weka documentation.

##### Details

There is a `predict`

method for
predicting from the fitted models.

`LinearRegression`

builds suitable linear regression models,
using the Akaike criterion for model selection.

`Logistic`

builds multinomial logistic regression models based on
ridge estimation (le Cessie and van Houwelingen, 1992).

The model formulae should only use `+` to indicate the variables
to be included.

##### Value

- A list inheriting from classes
`Weka_functions`

and`Weka_classifiers`

with components including classifier a reference (of class `jobjRef`

) to a Java object obtained by applying the Weka`buildClassifier`

method to build the specified model using the given control options.predictions a numeric vector or factor with the model predictions for the training instances (the results of calling the Weka `classifyInstance`

method for the built classifier and each instance).call the matched call.

*Documentation reproduced from package RWeka, version 0.1-0, License: GPL version 2 or newer*

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