Overview

This package is dedicated to classification analysis using decision trees. Aside from decision tree model itself and prediction function it has got all necessary supporting tools - data cleaning, transformation function, plot of the results and calculation of accuracy of predictions and confusion matrix.

Functionalities

The functionalities are as follows.

• Data Cleaning

require("tree3")
#> Loading required package: tree3
#> 
#> Attaching package: 'tree3'
#> The following object is masked from 'package:base':
#> 
#>     transform

data("bmarketing")
cleanedData <- clean(data = bmarketing,target_name = "y")

• Data Transforming

cleanedData$cons.price.id <- transform(cleanedData,column = "cons.price.idx")

• Finding a Model

treeModel <-  model(input_data = cleanedData,target_name="y")

• Getting the predictions

predictionData <-  predictions(dt_model = treeModel,data = cleanedData)

• Assessing the model accuracy

model_accuracy(real = cleanedData$y,pred = predictionData,chosenvar='yes')
#> $accuracy
#> [1] 0.9271668
#> 
#> $confusion_matrix
#>      pred
#> real    no  yes
#>   no  3583   85
#>   yes  215  236
#> 
#> $sensitivity
#> [1] 0.5232816
#> 
#> $specificity
#> [1] 0.9768266