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arules (version 1.2-1)

Mining Association Rules and Frequent Itemsets

Description

Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides interfaces to C implementations of the association mining algorithms Apriori and Eclat by C. Borgelt.

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Version

Install

install.packages('arules')

Monthly Downloads

19,711

Version

1.2-1

License

GPL-3

Maintainer

Michael Hahsler

Last Published

September 21st, 2015

Functions in arules (1.2-1)

support

Support Counting for Itemsets
itemFrequency

Getting Frequency/Support for Single Items
ASparameter-classes

Classes ``ASparameter'', ``APparameter'', ``ECparameter'' --- Specifying the `parameter' Argument of apriori() and eclat()
image

Visual Inspection of Binary Incidence Matrices
Income

Income Data Set
coverage

Calculate coverage for rules
hits

Computing Transaction Weights With HITS
APappearance-class

Class ``APappearance'' --- Specifying the `appearance' Argument of apriori()
aggregate

Aggregate Items Into Item Groups
AScontrol-classes

Classes ``AScontrol'', ``APcontrol'', ``ECcontrol'' --- Specifying the `control' Argument of apriori() and eclat()
interestMeasure

Calculating various additional interest measures
eclat

Mining Associations with Eclat
crossTable

Cross-tabulate joint occurrences across pairs of items
discretize

Convert a Continuous Variable into a Categorical Variable
Adult

Adult Data Set
is.closed

Find Closed Itemsets
proximity-classes

Classes ``dist'', ``ar_cross_dissimilarity'' and ``ar_similarity'' --- Proximity Matrices
duplicated

Find Duplicated Elements
is.maximal

Find Maximal Itemsets
random.transactions

Simulate a Random Transaction Data Set
ruleInduction

Rule Induction for a Set of Itemsets
size

Getting the Size of Each Element
unique

Remove Duplicated Elements from a Collection
read.transactions

Read Transaction Data
tidLists-class

Class ``tidLists'' --- Transaction ID Lists for Items/Itemsets
sample

Random Samples and Permutations
itemSetOperations

Itemwise Set Operations
associations-class

Class ``associations'' - A Set of Associations
supportingTransactions

Supporting Transactions
match

Value Matching
transactions-class

Class ``transactions'' --- Binary Incidence Matrix for Transactions
Groceries

Groceries Data Set
Epub

Epub Data Set
combine

Combining Objects
LIST

List Representation for Objects Based on ``itemMatrix''
merge

Merging (adding) items
itemCoding

Item Coding -- Handling Item Labels and Column IDs Conversions
write

Writes transactions or associations to disk
rules-class

Class ``rules'' --- A Set of Rules
weclat

Mining Associations from Weighted Transaction Data with Eclat
length

Getting the Number of Elements
apriori

Mining Associations with Apriori
is.superset

Find Super and Subsets
sort

Sorting Associations
predict

Model Predictions
setOperations

Set Operations
[-methods

Methods for "[": Extraction or Subsetting in Package 'arules'
itemsets-class

Class ``itemsets'' --- A Set of Itemsets
SunBai

The SunBai Data Set
affinity

Computing Affinity Between Items
Mushroom

Mushroom Data Set
dissimilarity

Dissimilarity Computation
read.PMML

Read and Write PMML
itemFrequencyPlot

Creating a Item Frequencies/Support Bar Plot
abbreviate

Abbreviate function for item labels in transactions, itemMatrix and rules
addComplement

Add Complement-items to Transactions
inspect

Display Associations and Transactions in Readable Form
itemMatrix-class

Class ``itemMatrix'' --- Sparse Binary Incidence Matrix to Represent Sets of Items
subset

Subsetting Itemsets, Rules and Transactions