classification_model: Generic function for creating a classification model

In sjoerdvds/crtests: Classification and Regression Tests

Description

Generic function for creating a classification model

Usage

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

sjoerdvds/crtests documentation built on May 30, 2019, 12:05 a.m.