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arules (version 1.0-1)

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

18,309

Version

1.0-1

License

GPL-2

Maintainer

Michael Hahsler

Last Published

December 3rd, 2009

Functions in arules (1.0-1)

Writes transactions or associations to disk

Computing Affinity Between Items

Income Data Set

Random Samples and Permutations

Cross-tabulate jount occurences across pairs of items

itemFrequencyPlot

Creating a Item Frequencies/Support Bar Plot

Merging (adding) items

AScontrol-classes

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

Subsetting Itemsets, Rules and Transactions

Find Closed Itemsets

associations-class

Class ``associations'' - A Set of Associations

Visual Inspection of Binary Incidence Matrices

interestMeasure

Calculating various additional interest measures

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

Aggregate Items Into Item Groups

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

Model Predictions

Groceries Data Set

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

Support Counting for Itemsets

Mining Associations with Eclat

random.transactions

Simulate a Random Transaction Data Set

List Representation for Objects Based on ``itemMatrix''

ASparameter-classes

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

Combining Objects

Find Duplicated Elements

Find Super and Subsets

Convert a Continuous Variable into a Categorical Variable

transactions-class

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

Convert a Continuous Variable into a Categorical Variable

Calculate coverage for rules

read.transactions

Read Transaction Data

Getting Frequency/Support for Single Items

Rule Induction for a Set of Itemsets

Find Maximal Itemsets

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

Display Associations and Transactions in Readable Form

itemMatrix-class

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

Item Coding -- Handling Item Labels and Column IDs Conversions

Getting the Size of Each Element

proximity-classes

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

Remove Duplicated Elements from a Collection

APappearance-class

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

Add Complement-items to Transactions

Mining Associations with Apriori

Dissimilarity Computation

Getting the Number of Elements

Sorting Associations

supportingTransactions

Supporting Transactions

Read and Write PMML