Association rule mining in Golang
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datasets
.travis.yml
README.md
arguments.go
arm.go
fptree.go
itemizer.go
itemsets.go
itemsets_test.go
rules.go
rules_test.go

README.md

arm-go

Build Status

An implementation of FPGrowth frequent pattern generation algorithm, along with association rule generation, in Go.

This finds relationships of the form "people who buy X also buy Y", and also determines the strengths (confidence, lift, support) of those relationships.

For an overview of assocation rule mining, see Chapter 5 of Introduction to Data Mining, Kumar et al: Association Analysis: Basic Concepts and Algorithms.

To build, download and install Go and clone this repository to $GO_PATH/src/arm-go, and build with:

  $ go build arm-go

You can then run from the command line, for example:

  $ ./arm-go --input datasets/kosarak.csv \
             --output rules \
             --itemsets itemsets \
             --min-support 0.05 \
             --min-confidence 0.05 \
             --min-lift 1.5

To run unit tests:

  $ go test