classification_model: Generic function for creating a classification model

Description Usage Arguments Value Methods (by class)

Description

Generic function for creating a classification model

Usage

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classification_model(method, test, x, y, training_data, ...)

## Default S3 method:
classification_model(method, test, x, y, training_data, ...)

## S3 method for class 'rpart'
classification_model(method, test, x, y, training_data, ...)

## S3 method for class 'boosting'
classification_model(method, test, x, y, training_data, ...)

Arguments

method

The method for classification.

test

The test being conducted

x

The independent variables.

y

The dependent (class) variable. Should be a factor for most algorithms

training_data

The complete data set for training

...

Extra arguments to pass to the classification algorithm

Value

The produced model

Methods (by class)

  • default: Default function for creating a classification model

    get s the method and calls it using x, y, and data

  • rpart: Rpart specific function for creating a classification model

    RPart requires a formula for classification, which is not provided by the default function

  • boosting: Create a classification model using Freund & Schapire's adaboost.M1



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