bank

datasets

Create, visualise, and test fast and frugal decision trees (FFTrees). FFTrees are very simple decision trees for
classifying cases (i.e.; breast cancer patients) into one of two classes (e.g.;
no cancer vs. true cancer) based on a small number of cues (e.g.; test results). FFTrees can be preferable to more complex algorithms because they are easy to communicate, require very little information, and are
robust against overfitting.

Nathaniel Phillips

FFTrees

Generate, Visualise, and Compare Fast and Frugal Decision Trees

bank function

A data frame containing 45,211 rows and 17 columns<dl class="dl-horizontal">
 <dt>age</dt><dd>numeric</dd>
 <dt>job</dt><dd>character</dd>
 <dt>marital</dt><dd>character - marital status</dd>
 <dt>education</dt><dd>character - education level</dd>
 <dt>default</dt><dd>character - has credit in default</dd>
 <dt>balance</dt><dd>numeric - balance of the loan</dd>
 <dt>housing</dt><dd>character - housing status</dd>
 <dt>loan</dt><dd>character - has a personal loan</dd>
 <dt>contact</dt><dd>character - contact communication type</dd>
 <dt>day</dt><dd>numeric - day in month last contacted</dd>
 <dt>month</dt><dd>character - last contact month</dd>
 <dt>duration</dt><dd>numeric - last contact duration in seconds</dd>
 <dt>campaign</dt><dd>numeric -number of contacts performed during this campaign for this client</dd>
 <dt>pdays</dt><dd>numeric - number of days that passed after the client was last contacted from a previous campaign (-1 means not previously contacted)</dd>
 <dt>previous</dt><dd>numeric - number of previous contacts</dd>
 <dt>poutcome</dt><dd>character - outcome of previous contact</dd>
 <dt>y</dt><dd>character - did the client subscribe to a term deposit?</dd>
 ...
</dl>

Format

A bank marketing dataset — bank

A data frame containing 45,211 rows and 17 columns<dl class='dl-horizontal'>
 <dt>age</dt><dd>numeric</dd>
 <dt>job</dt><dd>character</dd>
 <dt>marital</dt><dd>character - marital status</dd>
 <dt>education</dt><dd>character - education level</dd>
 <dt>default</dt><dd>character - has credit in default</dd>
 <dt>balance</dt><dd>numeric - balance of the loan</dd>
 <dt>housing</dt><dd>character - housing status</dd>
 <dt>loan</dt><dd>character - has a personal loan</dd>
 <dt>contact</dt><dd>character - contact communication type</dd>
 <dt>day</dt><dd>numeric - day in month last contacted</dd>
 <dt>month</dt><dd>character - last contact month</dd>
 <dt>duration</dt><dd>numeric - last contact duration in seconds</dd>
 <dt>campaign</dt><dd>numeric -number of contacts performed during this campaign for this client</dd>
 <dt>pdays</dt><dd>numeric - number of days that passed after the client was last contacted from a previous campaign (-1 means not previously contacted)</dd>
 <dt>previous</dt><dd>numeric - number of previous contacts</dd>
 <dt>poutcome</dt><dd>character - outcome of previous contact</dd>
 <dt>y</dt><dd>character - did the client subscribe to a term deposit?</dd>
 ...
</dl>

bank: A bank marketing dataset

Description

Usage

Arguments

Format