SunBai: The SunBai Data Set

Description Usage Details Source See Also Examples

Description

A small example database for weighted association rule mining provided as an object of class transactions.

Usage

1

Details

The data set contains the example database described in the paper by K. Sun and F.Bai for illustration of the concepts of weighted association rule mining. weight stored as transaction information denotes the transaction weights obtained using the HITS algorithm.

Source

K. Sun and F. Bai (2008). Mining Weighted Association Rules without Preassigned Weights. IEEE Transactions on Knowledge and Data Engineering, 4 (30), 489–495.

See Also

Class transactions, method transactionInfo, function hits.

Examples

1
2
3
4
5

Example output

Loading required package: Matrix

Attaching package: 'arules'

The following objects are masked from 'package:base':

    abbreviate, write

transactions as itemMatrix in sparse format with
 6 rows (elements/itemsets/transactions) and
 8 columns (items) and a density of 0.375 

most frequent items:
      A       C       G       B       F (Other) 
      4       3       3       2       2       4 

element (itemset/transaction) length distribution:
sizes
1 2 3 4 5 
1 1 2 1 1 

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   1.00    2.25    3.00    3.00    3.75    5.00 

includes extended item information - examples:
  labels
1      A
2      B
3      C

includes extended transaction information - examples:
  transactionID    weight
1           100 0.5176528
2           200 0.4362571
3           300 0.2321374
    items       transactionID weight   
[1] {A,B,C,D,E} 100           0.5176528
[2] {C,F,G}     200           0.4362571
[3] {A,B}       300           0.2321374
[4] {A}         400           0.1476262
[5] {C,F,G,H}   500           0.5440458
[6] {A,G,H}     600           0.4123691
  transactionID    weight
1           100 0.5176528
2           200 0.4362571
3           300 0.2321374
4           400 0.1476262
5           500 0.5440458
6           600 0.4123691

arules documentation built on Nov. 17, 2017, 6:02 a.m.