SequentialRules: A function to find frequential rules using the wonderful spmf...

In MGousseff/r2spmf: Links R 2 the SPMF Library for frequent itemsets and sequences mining

Description

This function sends a list of sequences to spmf and gets back Sequential Rules sequences with their support and confidence.

Usage

SequentialRules(x, algo, minsup = 0.5, minconf = 0.6, clean = F,
  windowSize = "")

Arguments

x	is the output of the function df2SPMFSequence function. It must contains a toSendSPMF storing a tibble with a basket column. This basket is sent to spmf java library.
algo	is the name of the algorithm to be used. The possible values are : Please check SPMF documentation at http://www.philippe-fournier-viger.com/spmf/index.php?link=documentation.php
minsup	is the value of the minimum support for a sequence to be seen as frequent. To get all the sequences present in more than 40 percent of the database sequences, type either "40%" or "0.4"
clean	if clean=F the text files sent to and received from spmf will be kept in the working directory.
windowSize	the TRuleGrowth searches for rules X==>Y within a given window size, based on the sequences who contains all the items of X before all the items of Y whithin the windowsize.
Those	time parameters are only considered when the input is a timed sequence. The only algorithme to be used are then "Fournier08-Closed+time" and "HirateYamana"

Value

a dataframe with three columns. sequence contains all the frequent sequences. support is the number of times this sequence occurs, and frequence is support divided by the total number of sequences

MGousseff/r2spmf documentation built on May 26, 2019, 11:58 p.m.