arules (version 1.0-12)

Income: Income Data Set

Description

The IncomeESL data set originates from an example in the book The Elements of Statistical Learning (see Section source). The data set is an extract from this survey. It consists of 8993 instances (obtained from the original data set with 9409 instances, by removing those observations with the annual income missing) with 14 demographic attributes. The data set is a good mixture of categorical and continuous variables with a lot of missing data. This is characteristic of data mining applications. The Income data set contains the data already prepared and coerced to transactions.

Usage

data("Income")
data("IncomeESL")

source

Impact Resources, Inc., Columbus, OH (1987).

Obtained from the web site of the book: Hastie, T., Tibshirani, R. & Friedman, J. (2001) The Elements of Statistical Learning. Springer-Verlag. (http://www-stat.stanford.edu/~tibs/ElemStatLearn/; called Marketing)

Details

To create Income (the transactions object), the original data frame in IncomeESL is prepared in a similar way as described in The Elements of Statistical Learning. We removed cases with missing values and cut each ordinal variable (age, education, income, years in bay area, number in household, and number of children) at its median into two values (see Section examples).

Examples

data("IncomeESL")
IncomeESL[1:3, ]

## remove incomplete cases
IncomeESL <- IncomeESL[complete.cases(IncomeESL), ]

## preparing the data set
IncomeESL[["income"]] <- factor((as.numeric(IncomeESL[["income"]]) > 6) +1,
  levels = 1 : 2 , labels = c("$0-$40,000", "$40,000+"))
	  
IncomeESL[["age"]] <- factor((as.numeric(IncomeESL[["age"]]) > 3) +1,
  levels = 1 : 2 , labels = c("14-34", "35+"))

IncomeESL[["education"]] <- factor((as.numeric(IncomeESL[["education"]]) > 4) +1,
  levels = 1 : 2 , labels = c("no college graduate", "college graduate"))

IncomeESL[["years in bay area"]] <- factor(
  (as.numeric(IncomeESL[["years in bay area"]]) > 4) +1,
  levels = 1 : 2 , labels = c("1-9", "10+"))

IncomeESL[["number in household"]] <- factor(
  (as.numeric(IncomeESL[["number in household"]]) > 3) +1,
  levels = 1 : 2 , labels = c("1", "2+"))

IncomeESL[["number of children"]] <- factor(
  (as.numeric(IncomeESL[["number of children"]]) > 1) +0,
  levels = 0 : 1 , labels = c("0", "1+"))
	
##  creating transactions
Income <- as(IncomeESL, "transactions")
Income