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arules (version 1.3-0)

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

25,744

Version

1.3-0

License

GPL-3

Maintainer

Michael Hahsler

Last Published

November 14th, 2015

Functions in arules (1.3-0)

AScontrol-classes

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

Getting Frequency/Support for Single Items
image

Visual Inspection of Binary Incidence Matrices
setOperations

Set Operations
inspect

Display Associations and Transactions in Readable Form
read.PMML

Read and Write PMML
predict

Model Predictions
discretize

Convert a Continuous Variable into a Categorical Variable
LIST

List Representation for Objects Based on ``itemMatrix''
itemsets-class

Class ``itemsets'' --- A Set of Itemsets
rules-class

Class ``rules'' --- A Set of Rules
tidLists-class

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

Subsetting Itemsets, Rules and Transactions
APappearance-class

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

Sorting Associations
match

Value Matching
affinity

Computing Affinity Between Items
random.transactions

Simulate a Random Transaction Data Set
hierarchy

Aggregate Items Into Hierarchical Item Groups
ASparameter-classes

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

Mining Associations with Apriori
Adult

Adult Data Set
coverage

Calculate coverage for rules
supportingTransactions

Supporting Transactions
Epub

Epub Data Set
Mushroom

Mushroom Data Set
Income

Income Data Set
sample

Random Samples and Permutations
itemSetOperations

Itemwise Set Operations
eclat

Mining Associations with Eclat
itemCoding

Item Coding -- Handling Item Labels and Column IDs Conversions
[-methods

Methods for "[": Extraction or Subsetting in Package 'arules'
addComplement

Add Complement-items to Transactions
read.transactions

Read Transaction Data
weclat

Mining Associations from Weighted Transaction Data with Eclat
size

Getting the Size of Each Element
merge

Merging (adding) items
support

Support Counting for Itemsets
dissimilarity

Dissimilarity Computation
abbreviate

Abbreviate function for item labels in transactions, itemMatrix and associations
crossTable

Cross-tabulate joint occurrences across pairs of items
proximity-classes

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

Rule Induction for a Set of Itemsets
is.maximal

Find Maximal Itemsets
length

Getting the Number of Elements
Groceries

Groceries Data Set
associations-class

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

Creating a Item Frequencies/Support Bar Plot
unique

Remove Duplicated Elements from a Collection
is.closed

Find Closed Itemsets
hits

Computing Transaction Weights With HITS
itemMatrix-class

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

Calculating various additional interest measures
SunBai

The SunBai Data Set
duplicated

Find Duplicated Elements
write

Writes transactions or associations to disk
combine

Combining Objects
is.superset

Find Super and Subsets
transactions-class

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